Back to Multiple platform build/check report for BioC 3.15 |
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This page was generated on 2022-10-19 13:20:23 -0400 (Wed, 19 Oct 2022).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 20.04.5 LTS) | x86_64 | 4.2.1 (2022-06-23) -- "Funny-Looking Kid" | 4386 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.2.1 (2022-06-23 ucrt) -- "Funny-Looking Kid" | 4138 |
merida1 | macOS 10.14.6 Mojave | x86_64 | 4.2.1 (2022-06-23) -- "Funny-Looking Kid" | 4205 |
Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X |
To the developers/maintainers of the HPiP package: - Please allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.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 911/2140 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.2.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 20.04.5 LTS) / x86_64 | OK | OK | OK | |||||||||
palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | |||||||||
merida1 | macOS 10.14.6 Mojave / x86_64 | OK | OK | OK | OK | |||||||||
Package: HPiP |
Version: 1.2.0 |
Command: /home/biocbuild/bbs-3.15-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.15-bioc/R/library --no-vignettes --timings HPiP_1.2.0.tar.gz |
StartedAt: 2022-10-18 20:08:45 -0400 (Tue, 18 Oct 2022) |
EndedAt: 2022-10-18 20:13:20 -0400 (Tue, 18 Oct 2022) |
EllapsedTime: 274.6 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.15-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.15-bioc/R/library --no-vignettes --timings HPiP_1.2.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.15-bioc/meat/HPiP.Rcheck’ * using R version 4.2.1 (2022-06-23) * using platform: x86_64-pc-linux-gnu (64-bit) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘HPiP/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘HPiP’ version ‘1.2.0’ * package encoding: UTF-8 * 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 ‘HPiP’ 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 ... NOTE Package unavailable to check Rd xrefs: ‘ftrCOOL’ * 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 R/sysdata.rda ... OK * checking files in ‘vignettes’ ... OK * checking examples ... OK Examples with CPU (user + system) or elapsed time > 5s user system elapsed corr_plot 35.591 0.484 36.078 FSmethod 34.413 0.984 35.398 var_imp 33.724 0.884 34.610 pred_ensembel 13.984 0.646 10.559 enrichfindP 0.431 0.033 11.590 * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘runTests.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: 1 NOTE See ‘/home/biocbuild/bbs-3.15-bioc/meat/HPiP.Rcheck/00check.log’ for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.15-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.15-bioc/R/library’ * installing *source* package ‘HPiP’ ... ** using staged installation ** 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 ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.2.1 (2022-06-23) -- "Funny-Looking Kid" 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. > BiocGenerics:::testPackage('HPiP') No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE avNNet Loading required package: ggplot2 Loading required package: lattice Fitting Repeat 1 # weights: 103 initial value 95.067599 final value 94.473118 converged Fitting Repeat 2 # weights: 103 initial value 95.822231 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 107.788814 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 97.446903 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 96.165612 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 108.704652 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 99.781818 iter 10 value 88.014067 iter 20 value 85.684835 final value 85.683709 converged Fitting Repeat 3 # weights: 305 initial value 96.739410 final value 94.402440 converged Fitting Repeat 4 # weights: 305 initial value 105.886146 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 95.665927 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 97.224090 iter 10 value 94.061206 iter 20 value 92.697509 iter 30 value 92.478276 final value 92.478198 converged Fitting Repeat 2 # weights: 507 initial value 102.974296 final value 94.322897 converged Fitting Repeat 3 # weights: 507 initial value 97.394634 iter 10 value 93.820496 final value 93.818593 converged Fitting Repeat 4 # weights: 507 initial value 99.294861 iter 10 value 93.730209 iter 20 value 92.882184 iter 30 value 92.796983 final value 92.796400 converged Fitting Repeat 5 # weights: 507 initial value 107.169097 final value 94.473118 converged Fitting Repeat 1 # weights: 103 initial value 101.999713 iter 10 value 94.486706 iter 20 value 93.843534 iter 30 value 90.679492 iter 40 value 85.771454 iter 50 value 84.388849 iter 60 value 84.004209 iter 70 value 83.903313 iter 80 value 83.491931 iter 90 value 83.386721 iter 100 value 83.327566 final value 83.327566 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 98.125877 iter 10 value 94.488737 iter 20 value 92.373925 iter 30 value 89.726621 iter 40 value 87.352127 iter 50 value 85.843929 iter 60 value 85.399669 iter 70 value 85.346948 iter 80 value 85.318455 iter 90 value 85.292743 iter 100 value 85.189206 final value 85.189206 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 98.483595 iter 10 value 94.478461 iter 20 value 94.029116 iter 30 value 91.918413 iter 40 value 87.862436 iter 50 value 86.215404 iter 60 value 85.640696 iter 70 value 85.603818 iter 80 value 85.421084 final value 85.378136 converged Fitting Repeat 4 # weights: 103 initial value 104.781774 iter 10 value 94.455119 iter 20 value 93.936931 iter 30 value 93.056496 iter 40 value 92.946093 iter 50 value 86.999299 iter 60 value 86.367658 iter 70 value 85.313844 iter 80 value 84.763153 iter 90 value 84.680051 final value 84.667974 converged Fitting Repeat 5 # weights: 103 initial value 102.583485 iter 10 value 93.902508 iter 20 value 87.141991 iter 30 value 86.832782 iter 40 value 86.129914 iter 50 value 85.734320 iter 60 value 85.208140 iter 70 value 85.069996 iter 80 value 84.924714 iter 90 value 84.853138 final value 84.852400 converged Fitting Repeat 1 # weights: 305 initial value 114.138299 iter 10 value 94.459749 iter 20 value 93.289381 iter 30 value 90.272159 iter 40 value 86.169760 iter 50 value 85.401710 iter 60 value 84.061201 iter 70 value 82.021887 iter 80 value 81.893265 iter 90 value 81.723579 iter 100 value 81.636408 final value 81.636408 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 108.309250 iter 10 value 94.525469 iter 20 value 93.602504 iter 30 value 88.753210 iter 40 value 87.208940 iter 50 value 86.431962 iter 60 value 83.761623 iter 70 value 82.890230 iter 80 value 82.333565 iter 90 value 81.893883 iter 100 value 81.615014 final value 81.615014 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 103.762464 iter 10 value 94.747509 iter 20 value 94.350344 iter 30 value 90.324508 iter 40 value 89.358169 iter 50 value 87.208724 iter 60 value 83.134550 iter 70 value 82.305779 iter 80 value 82.220385 iter 90 value 82.122921 iter 100 value 81.920687 final value 81.920687 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 103.586976 iter 10 value 94.468461 iter 20 value 93.533476 iter 30 value 88.359873 iter 40 value 85.396823 iter 50 value 84.344336 iter 60 value 83.484789 iter 70 value 82.748762 iter 80 value 82.137075 iter 90 value 81.586617 iter 100 value 81.557401 final value 81.557401 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 104.379218 iter 10 value 90.132712 iter 20 value 86.919402 iter 30 value 86.718406 iter 40 value 86.239654 iter 50 value 85.790829 iter 60 value 85.113715 iter 70 value 83.396603 iter 80 value 82.562308 iter 90 value 81.450610 iter 100 value 81.217765 final value 81.217765 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 109.135083 iter 10 value 94.290329 iter 20 value 89.097877 iter 30 value 85.288082 iter 40 value 83.300315 iter 50 value 82.916577 iter 60 value 82.057294 iter 70 value 81.506711 iter 80 value 81.337101 iter 90 value 81.309261 iter 100 value 81.285664 final value 81.285664 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 102.782462 iter 10 value 94.882775 iter 20 value 89.153253 iter 30 value 87.416628 iter 40 value 85.861667 iter 50 value 84.757454 iter 60 value 83.264531 iter 70 value 82.508494 iter 80 value 81.671311 iter 90 value 81.223014 iter 100 value 81.048073 final value 81.048073 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 128.555935 iter 10 value 95.981621 iter 20 value 93.367528 iter 30 value 88.397602 iter 40 value 88.196035 iter 50 value 86.033551 iter 60 value 85.924970 iter 70 value 85.648156 iter 80 value 84.927416 iter 90 value 83.596877 iter 100 value 82.831035 final value 82.831035 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 126.446562 iter 10 value 95.221559 iter 20 value 94.303720 iter 30 value 87.110303 iter 40 value 85.757105 iter 50 value 84.984139 iter 60 value 84.506779 iter 70 value 83.447668 iter 80 value 82.213420 iter 90 value 81.910488 iter 100 value 81.760524 final value 81.760524 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 126.071856 iter 10 value 94.409331 iter 20 value 89.299964 iter 30 value 86.362285 iter 40 value 85.345808 iter 50 value 85.221071 iter 60 value 85.121422 iter 70 value 85.022287 iter 80 value 84.675815 iter 90 value 83.928265 iter 100 value 81.778731 final value 81.778731 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 111.420894 iter 10 value 94.474778 iter 20 value 94.473269 iter 30 value 94.473136 final value 94.473132 converged Fitting Repeat 2 # weights: 103 initial value 106.797498 final value 94.485839 converged Fitting Repeat 3 # weights: 103 initial value 100.188660 iter 10 value 94.485768 final value 94.484350 converged Fitting Repeat 4 # weights: 103 initial value 94.935538 final value 94.483893 converged Fitting Repeat 5 # weights: 103 initial value 98.787758 final value 94.486077 converged Fitting Repeat 1 # weights: 305 initial value 104.633595 iter 10 value 94.489076 iter 20 value 94.471802 iter 30 value 91.738949 iter 40 value 91.138085 iter 50 value 91.128591 iter 60 value 88.544929 iter 70 value 86.502729 iter 80 value 86.491336 final value 86.491227 converged Fitting Repeat 2 # weights: 305 initial value 95.536904 iter 10 value 94.489089 iter 20 value 93.697858 iter 30 value 85.552728 iter 40 value 85.451766 iter 50 value 85.448813 iter 60 value 84.404390 iter 70 value 84.404026 iter 80 value 84.243260 iter 90 value 83.320581 iter 100 value 83.305055 final value 83.305055 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 105.387279 iter 10 value 94.477964 iter 20 value 94.470527 iter 30 value 87.726158 iter 40 value 86.542848 final value 86.540350 converged Fitting Repeat 4 # weights: 305 initial value 101.074740 iter 10 value 94.328300 iter 20 value 94.327922 iter 30 value 94.327108 iter 40 value 94.325594 iter 50 value 89.586301 iter 60 value 88.328906 iter 70 value 87.994168 iter 80 value 86.054702 iter 90 value 86.034847 final value 86.034841 converged Fitting Repeat 5 # weights: 305 initial value 104.385330 iter 10 value 94.489163 iter 20 value 94.484350 iter 30 value 88.051154 iter 40 value 87.602038 iter 50 value 85.790250 iter 60 value 85.788048 iter 70 value 85.784754 iter 80 value 84.636821 iter 90 value 83.535879 iter 100 value 83.531793 final value 83.531793 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 107.876180 iter 10 value 94.048458 iter 20 value 93.394613 iter 30 value 92.856706 iter 40 value 92.845520 iter 50 value 92.837765 iter 60 value 92.587362 iter 70 value 90.648775 iter 80 value 86.541315 iter 90 value 86.269511 iter 100 value 85.724304 final value 85.724304 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 106.034105 iter 10 value 94.450713 iter 20 value 93.681387 iter 30 value 86.498670 iter 40 value 85.363496 iter 50 value 85.130087 iter 60 value 85.122666 iter 70 value 85.117586 iter 80 value 85.116753 iter 90 value 82.694704 iter 100 value 80.557185 final value 80.557185 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 94.601376 iter 10 value 94.481589 iter 20 value 94.175135 iter 30 value 87.248799 iter 40 value 84.676021 iter 50 value 82.679999 iter 60 value 82.391771 iter 70 value 82.304916 iter 80 value 82.240574 iter 90 value 82.237920 final value 82.237872 converged Fitting Repeat 4 # weights: 507 initial value 106.679700 iter 10 value 94.493037 iter 20 value 94.218504 iter 30 value 85.439360 iter 40 value 85.160884 final value 85.159859 converged Fitting Repeat 5 # weights: 507 initial value 100.436739 iter 10 value 94.492170 iter 20 value 94.437318 iter 30 value 85.591702 final value 85.525279 converged Fitting Repeat 1 # weights: 103 initial value 104.015663 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 95.593853 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 97.795225 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 102.055811 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 96.504967 final value 94.275362 converged Fitting Repeat 1 # weights: 305 initial value 106.175907 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 97.821203 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 95.957385 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 109.783916 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 107.531110 final value 94.275362 converged Fitting Repeat 1 # weights: 507 initial value 117.468876 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 97.563958 final value 94.275362 converged Fitting Repeat 3 # weights: 507 initial value 94.866424 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 113.714624 iter 10 value 94.484462 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 107.315525 final value 94.274404 converged Fitting Repeat 1 # weights: 103 initial value 109.097387 iter 10 value 94.462678 iter 20 value 92.535525 iter 30 value 90.333639 iter 40 value 88.195052 iter 50 value 84.949756 iter 60 value 84.159245 iter 70 value 84.026441 iter 80 value 83.985057 iter 90 value 83.846644 iter 100 value 83.816243 final value 83.816243 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 100.879176 iter 10 value 94.539783 iter 20 value 94.464965 iter 30 value 91.923159 iter 40 value 83.099434 iter 50 value 82.454101 iter 60 value 82.182197 iter 70 value 81.551007 iter 80 value 80.110991 iter 90 value 79.956040 iter 100 value 79.850038 final value 79.850038 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 98.423416 iter 10 value 94.358994 iter 20 value 91.756726 iter 30 value 90.719028 iter 40 value 88.639139 iter 50 value 83.900211 iter 60 value 83.022206 iter 70 value 82.429592 iter 80 value 82.109217 iter 90 value 81.947697 final value 81.947626 converged Fitting Repeat 4 # weights: 103 initial value 110.269260 iter 10 value 95.215565 iter 20 value 94.314831 iter 30 value 90.534512 iter 40 value 89.871820 iter 50 value 85.320196 iter 60 value 83.948464 iter 70 value 83.870523 iter 80 value 83.847233 iter 90 value 83.817038 final value 83.813826 converged Fitting Repeat 5 # weights: 103 initial value 98.585392 iter 10 value 94.369258 iter 20 value 93.878964 iter 30 value 93.537662 iter 40 value 91.919157 iter 50 value 83.789662 iter 60 value 82.812813 iter 70 value 82.194584 iter 80 value 82.123458 iter 90 value 81.957774 final value 81.947626 converged Fitting Repeat 1 # weights: 305 initial value 111.003945 iter 10 value 94.491302 iter 20 value 94.214354 iter 30 value 93.568059 iter 40 value 93.489008 iter 50 value 93.078883 iter 60 value 91.234906 iter 70 value 87.991789 iter 80 value 84.623981 iter 90 value 81.449400 iter 100 value 80.385478 final value 80.385478 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 106.081148 iter 10 value 93.896966 iter 20 value 85.430644 iter 30 value 84.677494 iter 40 value 83.936354 iter 50 value 82.179552 iter 60 value 81.598247 iter 70 value 81.056577 iter 80 value 80.997860 iter 90 value 80.975859 iter 100 value 80.954319 final value 80.954319 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 103.456590 iter 10 value 94.959565 iter 20 value 84.946252 iter 30 value 81.432653 iter 40 value 78.804166 iter 50 value 78.604176 iter 60 value 78.569414 iter 70 value 78.441693 iter 80 value 78.301691 iter 90 value 78.216267 iter 100 value 78.089918 final value 78.089918 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 101.736627 iter 10 value 93.271485 iter 20 value 86.140314 iter 30 value 84.525107 iter 40 value 82.155484 iter 50 value 80.011109 iter 60 value 79.625342 iter 70 value 79.457891 iter 80 value 79.391769 iter 90 value 79.338736 iter 100 value 78.894093 final value 78.894093 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.904501 iter 10 value 94.562254 iter 20 value 94.512352 iter 30 value 84.156924 iter 40 value 83.570088 iter 50 value 81.955496 iter 60 value 81.073426 iter 70 value 80.764505 iter 80 value 79.966854 iter 90 value 79.606378 iter 100 value 79.411565 final value 79.411565 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 119.368950 iter 10 value 94.405380 iter 20 value 93.224469 iter 30 value 93.150247 iter 40 value 91.166596 iter 50 value 82.615073 iter 60 value 80.346694 iter 70 value 79.075640 iter 80 value 78.753917 iter 90 value 78.693233 iter 100 value 78.285114 final value 78.285114 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 120.405518 iter 10 value 97.981825 iter 20 value 93.400784 iter 30 value 88.685772 iter 40 value 84.881224 iter 50 value 84.585025 iter 60 value 84.281991 iter 70 value 81.731284 iter 80 value 80.458540 iter 90 value 79.958102 iter 100 value 79.797577 final value 79.797577 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 118.790094 iter 10 value 94.517745 iter 20 value 94.286092 iter 30 value 83.838286 iter 40 value 82.276672 iter 50 value 80.255302 iter 60 value 79.435773 iter 70 value 78.836423 iter 80 value 78.534031 iter 90 value 78.089958 iter 100 value 78.025961 final value 78.025961 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 103.831278 iter 10 value 89.634595 iter 20 value 86.398847 iter 30 value 85.588944 iter 40 value 83.316170 iter 50 value 79.817606 iter 60 value 79.095189 iter 70 value 78.552567 iter 80 value 78.361137 iter 90 value 78.106259 iter 100 value 77.763552 final value 77.763552 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 122.545446 iter 10 value 96.189322 iter 20 value 94.384108 iter 30 value 87.287796 iter 40 value 83.105782 iter 50 value 81.651506 iter 60 value 79.753133 iter 70 value 79.269166 iter 80 value 78.999660 iter 90 value 78.726411 iter 100 value 78.477124 final value 78.477124 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 98.205383 final value 94.485740 converged Fitting Repeat 2 # weights: 103 initial value 95.606632 iter 10 value 94.277331 iter 20 value 94.275489 iter 30 value 85.847277 iter 40 value 85.755561 iter 50 value 83.454165 iter 60 value 83.267158 iter 70 value 83.237322 iter 80 value 83.191440 iter 90 value 83.164976 iter 100 value 83.164838 final value 83.164838 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 95.754207 final value 94.485817 converged Fitting Repeat 4 # weights: 103 initial value 97.477874 final value 94.485687 converged Fitting Repeat 5 # weights: 103 initial value 95.531270 iter 10 value 94.485936 iter 20 value 94.396313 iter 30 value 92.521801 iter 40 value 92.495025 iter 50 value 92.494883 final value 92.493940 converged Fitting Repeat 1 # weights: 305 initial value 108.393114 iter 10 value 94.491129 iter 20 value 94.486084 final value 94.486082 converged Fitting Repeat 2 # weights: 305 initial value 112.903855 iter 10 value 94.280754 iter 20 value 94.275869 final value 94.275544 converged Fitting Repeat 3 # weights: 305 initial value 108.557298 iter 10 value 94.489413 iter 20 value 93.134381 iter 30 value 89.460837 iter 40 value 86.294827 iter 50 value 85.955241 iter 60 value 85.940882 iter 70 value 85.927926 iter 80 value 83.842647 iter 90 value 83.562097 final value 83.485118 converged Fitting Repeat 4 # weights: 305 initial value 101.518768 iter 10 value 94.489908 iter 20 value 94.289822 iter 30 value 81.591253 iter 40 value 79.730536 iter 50 value 79.667821 iter 60 value 79.667227 final value 79.667213 converged Fitting Repeat 5 # weights: 305 initial value 96.735448 iter 10 value 94.094155 iter 20 value 91.685115 iter 30 value 83.785516 iter 40 value 83.722272 iter 50 value 83.496082 iter 60 value 80.747367 iter 70 value 79.430372 iter 80 value 79.218618 iter 90 value 79.217135 iter 100 value 79.216293 final value 79.216293 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 95.628179 iter 10 value 93.988880 iter 20 value 93.953340 iter 30 value 93.694650 iter 40 value 93.693946 iter 40 value 93.693945 iter 40 value 93.693945 final value 93.693945 converged Fitting Repeat 2 # weights: 507 initial value 98.981383 iter 10 value 92.815899 iter 20 value 92.411750 iter 30 value 92.283503 iter 40 value 92.265718 iter 50 value 92.264932 iter 60 value 91.479370 iter 70 value 82.177383 iter 80 value 81.780057 iter 90 value 81.772840 iter 100 value 81.772481 final value 81.772481 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 95.986412 iter 10 value 94.482690 iter 20 value 90.452070 iter 30 value 89.134562 iter 40 value 88.399263 iter 50 value 87.766578 iter 60 value 87.746647 iter 70 value 87.597297 iter 80 value 87.556234 iter 90 value 87.553122 iter 100 value 84.052652 final value 84.052652 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 106.487802 iter 10 value 94.283859 iter 20 value 94.278815 iter 30 value 91.969895 iter 40 value 84.227525 iter 50 value 83.201399 iter 60 value 81.433221 iter 70 value 80.648380 iter 80 value 80.638577 iter 90 value 79.548824 final value 79.548609 converged Fitting Repeat 5 # weights: 507 initial value 102.950623 iter 10 value 94.284521 iter 20 value 94.174599 iter 30 value 92.304462 iter 40 value 89.865413 iter 50 value 86.508824 iter 60 value 83.159936 iter 70 value 82.008886 iter 80 value 81.125933 iter 90 value 81.022439 iter 100 value 80.687568 final value 80.687568 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.479162 final value 94.049020 converged Fitting Repeat 2 # weights: 103 initial value 94.329086 final value 94.008694 converged Fitting Repeat 3 # weights: 103 initial value 101.781067 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 101.697148 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 99.942443 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 95.719466 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 131.389618 iter 10 value 94.052910 iter 10 value 94.052910 iter 10 value 94.052910 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 104.645386 iter 10 value 92.924953 iter 20 value 92.811925 final value 92.811793 converged Fitting Repeat 4 # weights: 305 initial value 104.475911 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 117.526747 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 108.416284 final value 93.869755 converged Fitting Repeat 2 # weights: 507 initial value 96.569415 final value 94.052910 converged Fitting Repeat 3 # weights: 507 initial value 104.866407 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 118.622417 iter 10 value 91.363995 iter 20 value 87.383150 iter 30 value 86.641502 iter 40 value 86.619003 iter 50 value 86.618785 iter 50 value 86.618784 iter 50 value 86.618784 final value 86.618784 converged Fitting Repeat 5 # weights: 507 initial value 120.498160 final value 93.915746 converged Fitting Repeat 1 # weights: 103 initial value 106.689655 iter 10 value 94.058530 iter 20 value 93.530389 iter 30 value 88.801865 iter 40 value 85.473189 iter 50 value 83.544703 iter 60 value 83.400268 iter 70 value 83.364769 iter 80 value 83.350546 iter 90 value 83.344514 final value 83.344502 converged Fitting Repeat 2 # weights: 103 initial value 102.353042 iter 10 value 94.012844 iter 20 value 93.737414 iter 30 value 93.675098 iter 40 value 87.107053 iter 50 value 86.330970 iter 60 value 86.240477 iter 70 value 84.386907 iter 80 value 83.447211 iter 90 value 83.399796 iter 100 value 83.390054 final value 83.390054 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 100.720279 iter 10 value 94.057207 iter 20 value 92.369715 iter 30 value 86.246136 iter 40 value 86.099862 iter 50 value 85.953522 iter 60 value 85.364721 iter 70 value 84.159806 iter 80 value 83.543661 iter 90 value 83.409975 iter 100 value 83.385198 final value 83.385198 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 103.321517 iter 10 value 94.056147 iter 20 value 93.834716 iter 30 value 93.688443 iter 40 value 93.530867 iter 50 value 83.717263 iter 60 value 83.281084 iter 70 value 83.182236 iter 80 value 82.592874 iter 90 value 82.148306 iter 100 value 82.022813 final value 82.022813 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 97.448798 iter 10 value 94.056040 iter 20 value 93.777107 iter 30 value 93.739012 iter 40 value 93.731110 iter 50 value 93.730644 iter 60 value 92.526945 iter 70 value 85.069456 iter 80 value 83.493589 iter 90 value 83.406915 iter 100 value 83.346454 final value 83.346454 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 101.356208 iter 10 value 87.827873 iter 20 value 86.308525 iter 30 value 85.224794 iter 40 value 84.349313 iter 50 value 84.265595 iter 60 value 83.396474 iter 70 value 82.391914 iter 80 value 81.740509 iter 90 value 81.349766 iter 100 value 81.175117 final value 81.175117 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 100.166664 iter 10 value 94.182672 iter 20 value 85.536182 iter 30 value 84.354948 iter 40 value 84.237409 iter 50 value 83.963652 iter 60 value 82.854354 iter 70 value 81.710786 iter 80 value 81.296725 iter 90 value 81.038723 iter 100 value 80.871379 final value 80.871379 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 108.529038 iter 10 value 93.923405 iter 20 value 93.496904 iter 30 value 88.937036 iter 40 value 85.306677 iter 50 value 81.401619 iter 60 value 80.944143 iter 70 value 80.645390 iter 80 value 80.452475 iter 90 value 80.276791 iter 100 value 80.224559 final value 80.224559 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 118.095701 iter 10 value 94.241832 iter 20 value 86.339034 iter 30 value 84.707349 iter 40 value 84.516137 iter 50 value 81.656630 iter 60 value 81.109214 iter 70 value 80.700404 iter 80 value 80.526538 iter 90 value 80.502063 iter 100 value 80.499341 final value 80.499341 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 116.812027 iter 10 value 94.035633 iter 20 value 90.086950 iter 30 value 85.792431 iter 40 value 84.756574 iter 50 value 83.485317 iter 60 value 82.847721 iter 70 value 82.727675 iter 80 value 82.670695 iter 90 value 82.649624 iter 100 value 82.529937 final value 82.529937 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 115.035653 iter 10 value 94.012737 iter 20 value 86.241042 iter 30 value 84.179541 iter 40 value 83.074438 iter 50 value 81.951194 iter 60 value 80.615946 iter 70 value 80.216486 iter 80 value 80.090800 iter 90 value 80.029887 iter 100 value 79.960566 final value 79.960566 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 131.892361 iter 10 value 98.359685 iter 20 value 95.246706 iter 30 value 93.884402 iter 40 value 88.596217 iter 50 value 86.274684 iter 60 value 85.593800 iter 70 value 83.073898 iter 80 value 82.457977 iter 90 value 81.904695 iter 100 value 81.427942 final value 81.427942 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.050892 iter 10 value 93.963019 iter 20 value 86.117089 iter 30 value 83.986328 iter 40 value 82.952581 iter 50 value 82.793893 iter 60 value 82.756694 iter 70 value 82.709352 iter 80 value 82.566101 iter 90 value 82.042446 iter 100 value 81.184513 final value 81.184513 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 117.503376 iter 10 value 94.173080 iter 20 value 92.138527 iter 30 value 84.423570 iter 40 value 84.238942 iter 50 value 83.982728 iter 60 value 83.020125 iter 70 value 82.216262 iter 80 value 81.741937 iter 90 value 81.414200 iter 100 value 80.640360 final value 80.640360 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 109.318061 iter 10 value 92.686305 iter 20 value 85.715783 iter 30 value 85.565744 iter 40 value 84.206356 iter 50 value 82.480024 iter 60 value 82.205139 iter 70 value 82.042104 iter 80 value 81.648705 iter 90 value 80.823924 iter 100 value 80.365578 final value 80.365578 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.109895 final value 94.054643 converged Fitting Repeat 2 # weights: 103 initial value 97.705343 final value 94.054548 converged Fitting Repeat 3 # weights: 103 initial value 94.158104 final value 94.054531 converged Fitting Repeat 4 # weights: 103 initial value 102.189895 final value 94.054668 converged Fitting Repeat 5 # weights: 103 initial value 110.317488 final value 94.054383 converged Fitting Repeat 1 # weights: 305 initial value 96.093246 iter 10 value 94.033226 iter 20 value 94.028550 iter 30 value 93.625255 iter 40 value 92.592353 iter 50 value 91.389922 iter 60 value 90.870232 iter 70 value 90.818965 final value 90.818912 converged Fitting Repeat 2 # weights: 305 initial value 105.101779 iter 10 value 94.058181 iter 20 value 94.053280 iter 30 value 91.901871 iter 40 value 86.383872 iter 50 value 82.422961 iter 60 value 80.744002 iter 70 value 80.200728 iter 80 value 80.093650 iter 90 value 79.244234 iter 100 value 79.107640 final value 79.107640 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 95.431523 iter 10 value 94.058283 iter 20 value 94.052941 iter 30 value 93.932934 iter 40 value 93.711614 iter 50 value 93.702003 final value 93.697880 converged Fitting Repeat 4 # weights: 305 initial value 102.734622 iter 10 value 94.057744 iter 20 value 94.052938 iter 30 value 93.852710 iter 40 value 90.580233 iter 50 value 83.354923 iter 60 value 81.767783 iter 70 value 81.764529 iter 80 value 81.764325 final value 81.763975 converged Fitting Repeat 5 # weights: 305 initial value 97.231958 iter 10 value 94.057538 iter 20 value 93.703542 iter 30 value 85.362216 iter 40 value 84.350314 iter 50 value 84.342992 iter 60 value 84.342643 iter 70 value 82.132828 iter 80 value 81.682979 iter 90 value 81.669576 iter 100 value 81.669395 final value 81.669395 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 98.763132 iter 10 value 93.128881 iter 20 value 88.438367 iter 30 value 84.579772 iter 40 value 84.420581 iter 50 value 84.418253 iter 60 value 83.658815 iter 70 value 83.521762 iter 80 value 83.520188 iter 90 value 83.520001 iter 100 value 83.510306 final value 83.510306 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 107.447927 iter 10 value 94.061901 iter 20 value 94.042094 iter 30 value 93.643614 iter 30 value 93.643613 iter 30 value 93.643613 final value 93.643613 converged Fitting Repeat 3 # weights: 507 initial value 123.104572 iter 10 value 94.060697 iter 20 value 94.053214 iter 30 value 93.915843 iter 40 value 93.766018 iter 50 value 93.697982 final value 93.697981 converged Fitting Repeat 4 # weights: 507 initial value 99.727699 iter 10 value 94.061493 iter 20 value 93.706264 iter 30 value 83.623558 iter 40 value 83.362820 iter 50 value 83.355452 final value 83.324408 converged Fitting Repeat 5 # weights: 507 initial value 116.305404 iter 10 value 93.923586 iter 20 value 93.917179 iter 30 value 90.752875 iter 40 value 85.784878 iter 50 value 85.733103 iter 60 value 85.725199 iter 70 value 83.376215 iter 80 value 83.351103 iter 90 value 83.312024 iter 100 value 82.875056 final value 82.875056 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.829325 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 106.044857 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 105.354237 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 94.428283 iter 10 value 94.212650 final value 94.212644 converged Fitting Repeat 5 # weights: 103 initial value 110.144297 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 96.741716 final value 94.275362 converged Fitting Repeat 2 # weights: 305 initial value 103.426153 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 110.742080 iter 10 value 86.809509 iter 20 value 85.973837 iter 30 value 85.969019 iter 40 value 85.926751 final value 85.926160 converged Fitting Repeat 4 # weights: 305 initial value 97.038420 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 111.677090 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 109.921704 iter 10 value 94.444762 iter 20 value 94.275362 iter 20 value 94.275362 iter 20 value 94.275362 final value 94.275362 converged Fitting Repeat 2 # weights: 507 initial value 96.831298 final value 94.275362 converged Fitting Repeat 3 # weights: 507 initial value 120.577860 iter 10 value 94.484219 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 103.199845 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 95.645569 final value 94.275363 converged Fitting Repeat 1 # weights: 103 initial value 102.196274 iter 10 value 94.489471 iter 20 value 93.061274 iter 30 value 91.664677 iter 40 value 91.144409 iter 50 value 91.110351 iter 60 value 91.107651 iter 70 value 91.104459 iter 80 value 91.103930 final value 91.103912 converged Fitting Repeat 2 # weights: 103 initial value 119.632656 iter 10 value 94.491974 iter 20 value 91.566006 iter 30 value 90.857368 iter 40 value 90.814458 iter 50 value 87.450965 iter 60 value 87.185412 iter 70 value 84.015730 iter 80 value 83.952274 iter 90 value 83.737225 iter 100 value 83.707539 final value 83.707539 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 99.400296 iter 10 value 93.988355 iter 20 value 89.512988 iter 30 value 84.300315 iter 40 value 83.823545 iter 50 value 83.710702 iter 60 value 83.707520 final value 83.707518 converged Fitting Repeat 4 # weights: 103 initial value 98.168737 iter 10 value 94.093688 iter 20 value 86.313934 iter 30 value 83.745727 iter 40 value 83.468818 iter 50 value 82.378307 iter 60 value 81.871995 iter 70 value 81.457519 iter 80 value 81.412953 iter 90 value 81.375812 final value 81.374763 converged Fitting Repeat 5 # weights: 103 initial value 108.306344 iter 10 value 97.544147 iter 20 value 94.475493 iter 30 value 91.606002 iter 40 value 86.198483 iter 50 value 85.097669 iter 60 value 84.776929 iter 70 value 84.522484 iter 80 value 84.055638 iter 90 value 83.353442 iter 100 value 83.333061 final value 83.333061 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 101.263235 iter 10 value 94.495510 iter 20 value 89.926032 iter 30 value 87.158760 iter 40 value 86.113641 iter 50 value 85.030652 iter 60 value 82.590862 iter 70 value 80.992841 iter 80 value 80.540905 iter 90 value 80.210008 iter 100 value 79.997745 final value 79.997745 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 101.629315 iter 10 value 94.089098 iter 20 value 87.553802 iter 30 value 85.965337 iter 40 value 83.494111 iter 50 value 83.040682 iter 60 value 82.876252 iter 70 value 82.830125 iter 80 value 82.283024 iter 90 value 81.594711 iter 100 value 81.230984 final value 81.230984 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.828130 iter 10 value 94.382650 iter 20 value 90.376841 iter 30 value 88.562700 iter 40 value 87.591798 iter 50 value 86.725121 iter 60 value 83.858799 iter 70 value 81.417212 iter 80 value 80.384882 iter 90 value 80.258304 iter 100 value 80.204455 final value 80.204455 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 122.472371 iter 10 value 94.250414 iter 20 value 87.096386 iter 30 value 85.684242 iter 40 value 85.045791 iter 50 value 84.729640 iter 60 value 81.681426 iter 70 value 80.776580 iter 80 value 80.315910 iter 90 value 80.034724 iter 100 value 79.982310 final value 79.982310 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 107.746492 iter 10 value 94.155557 iter 20 value 85.802902 iter 30 value 84.190301 iter 40 value 83.741948 iter 50 value 82.701501 iter 60 value 81.573602 iter 70 value 81.422741 iter 80 value 80.692676 iter 90 value 80.357808 iter 100 value 80.247717 final value 80.247717 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 110.490094 iter 10 value 95.249036 iter 20 value 92.182939 iter 30 value 86.448511 iter 40 value 85.381150 iter 50 value 85.075754 iter 60 value 84.946137 iter 70 value 83.241293 iter 80 value 82.284789 iter 90 value 81.729419 iter 100 value 80.669255 final value 80.669255 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 106.886346 iter 10 value 94.336228 iter 20 value 84.522735 iter 30 value 83.187130 iter 40 value 82.379005 iter 50 value 82.031703 iter 60 value 81.342305 iter 70 value 80.790713 iter 80 value 80.665287 iter 90 value 80.622219 iter 100 value 80.608635 final value 80.608635 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 137.231725 iter 10 value 94.725988 iter 20 value 94.412133 iter 30 value 90.753809 iter 40 value 88.564649 iter 50 value 85.084089 iter 60 value 83.705301 iter 70 value 81.127574 iter 80 value 80.145282 iter 90 value 79.954882 iter 100 value 79.796236 final value 79.796236 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 110.565730 iter 10 value 94.071012 iter 20 value 88.446813 iter 30 value 85.873210 iter 40 value 85.071667 iter 50 value 83.165356 iter 60 value 81.260657 iter 70 value 80.387298 iter 80 value 79.738274 iter 90 value 79.498425 iter 100 value 79.384144 final value 79.384144 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 103.490717 iter 10 value 94.413253 iter 20 value 93.718877 iter 30 value 88.203518 iter 40 value 87.099459 iter 50 value 85.638132 iter 60 value 83.297224 iter 70 value 82.498538 iter 80 value 81.623750 iter 90 value 81.232474 iter 100 value 80.808167 final value 80.808167 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.667153 final value 94.485790 converged Fitting Repeat 2 # weights: 103 initial value 101.310852 final value 94.486028 converged Fitting Repeat 3 # weights: 103 initial value 97.930563 final value 94.486045 converged Fitting Repeat 4 # weights: 103 initial value 102.474121 final value 94.485874 converged Fitting Repeat 5 # weights: 103 initial value 102.549488 final value 94.485560 converged Fitting Repeat 1 # weights: 305 initial value 95.068436 iter 10 value 94.376792 iter 20 value 94.372650 iter 30 value 94.336065 iter 40 value 92.684847 iter 50 value 92.365947 iter 60 value 92.363800 final value 92.363789 converged Fitting Repeat 2 # weights: 305 initial value 100.362726 iter 10 value 93.706500 iter 20 value 87.453525 iter 30 value 87.370335 iter 40 value 86.050962 iter 50 value 85.831396 final value 85.800500 converged Fitting Repeat 3 # weights: 305 initial value 111.457340 iter 10 value 94.676552 iter 20 value 94.544886 iter 30 value 94.489969 iter 40 value 91.931107 iter 50 value 87.327525 iter 60 value 87.128210 iter 70 value 86.434985 iter 80 value 85.710108 iter 90 value 85.641883 iter 100 value 85.636396 final value 85.636396 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 121.973362 iter 10 value 94.184720 iter 20 value 94.184036 iter 30 value 94.179687 iter 40 value 94.158206 iter 50 value 84.781138 iter 60 value 84.616300 iter 70 value 84.614930 final value 84.614754 converged Fitting Repeat 5 # weights: 305 initial value 100.157557 iter 10 value 94.488074 iter 20 value 93.493646 iter 30 value 86.884954 iter 40 value 84.439646 iter 50 value 84.435287 iter 60 value 84.434837 final value 84.434685 converged Fitting Repeat 1 # weights: 507 initial value 105.944781 iter 10 value 94.491545 iter 20 value 94.415594 iter 30 value 91.279056 iter 40 value 85.291247 iter 50 value 84.343461 iter 60 value 84.341961 iter 70 value 84.083649 iter 80 value 83.400971 iter 90 value 82.589743 iter 100 value 82.448093 final value 82.448093 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 95.169621 iter 10 value 94.283638 iter 20 value 93.509686 iter 30 value 85.900222 iter 40 value 84.635075 iter 50 value 84.342163 final value 84.341112 converged Fitting Repeat 3 # weights: 507 initial value 103.110100 iter 10 value 91.573663 iter 20 value 91.192393 iter 30 value 91.156900 iter 40 value 91.155555 iter 50 value 91.127683 iter 60 value 91.104627 iter 70 value 91.103414 iter 80 value 91.103208 iter 90 value 91.098190 iter 100 value 91.097441 final value 91.097441 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 95.751235 iter 10 value 88.444475 iter 20 value 88.416006 iter 30 value 86.530877 iter 40 value 86.380081 iter 50 value 85.989350 iter 60 value 83.249661 iter 70 value 82.932556 iter 80 value 82.916731 iter 90 value 82.915581 iter 100 value 82.788738 final value 82.788738 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 98.589479 iter 10 value 92.223078 iter 20 value 91.330098 iter 30 value 91.233300 iter 40 value 91.227961 iter 50 value 91.226810 iter 60 value 91.225542 iter 70 value 91.224697 iter 80 value 91.224063 iter 90 value 91.223185 iter 100 value 85.097471 final value 85.097471 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.324158 final value 93.915746 converged Fitting Repeat 2 # weights: 103 initial value 105.405235 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 97.863625 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 103.060391 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 106.285732 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 109.985204 final value 93.628453 converged Fitting Repeat 2 # weights: 305 initial value 95.728354 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 99.995042 iter 10 value 93.309430 iter 20 value 93.159435 iter 30 value 93.105125 final value 93.104307 converged Fitting Repeat 4 # weights: 305 initial value 97.909509 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 104.415110 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 112.153110 final value 93.915746 converged Fitting Repeat 2 # weights: 507 initial value 102.118724 iter 10 value 89.729438 iter 20 value 88.874590 iter 30 value 88.868400 final value 88.868334 converged Fitting Repeat 3 # weights: 507 initial value 96.771757 final value 93.988096 converged Fitting Repeat 4 # weights: 507 initial value 117.872242 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 100.678408 final value 93.915746 converged Fitting Repeat 1 # weights: 103 initial value 100.267685 iter 10 value 94.025271 iter 20 value 92.669514 iter 30 value 89.264204 iter 40 value 87.690927 iter 50 value 87.240086 iter 60 value 87.082430 iter 70 value 85.727380 iter 80 value 84.655854 iter 90 value 84.509589 iter 100 value 84.245818 final value 84.245818 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 100.859751 iter 10 value 94.056876 iter 20 value 94.039661 iter 30 value 93.338680 iter 40 value 89.584779 iter 50 value 89.309853 iter 60 value 85.356141 iter 70 value 84.681817 iter 80 value 84.314243 iter 90 value 84.084450 iter 100 value 84.058251 final value 84.058251 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 107.792397 iter 10 value 93.989560 iter 20 value 85.915369 iter 30 value 85.562447 iter 40 value 85.346190 iter 50 value 85.245952 iter 60 value 84.973307 iter 70 value 84.222724 iter 80 value 84.211711 iter 90 value 84.169879 iter 100 value 84.072839 final value 84.072839 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 99.591646 iter 10 value 94.056851 iter 20 value 93.655444 iter 30 value 90.319479 iter 40 value 86.727755 iter 50 value 84.687517 iter 60 value 84.399963 iter 70 value 84.171254 iter 80 value 84.094526 iter 90 value 82.868355 iter 100 value 82.565500 final value 82.565500 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 106.311323 iter 10 value 88.648078 iter 20 value 86.678947 iter 30 value 86.343355 iter 40 value 86.020892 iter 50 value 85.458600 iter 60 value 85.428712 final value 85.428686 converged Fitting Repeat 1 # weights: 305 initial value 99.899461 iter 10 value 92.179623 iter 20 value 86.581765 iter 30 value 85.952147 iter 40 value 85.112831 iter 50 value 84.495744 iter 60 value 83.426482 iter 70 value 82.020006 iter 80 value 81.903073 iter 90 value 81.539223 iter 100 value 81.447631 final value 81.447631 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 110.707446 iter 10 value 93.929000 iter 20 value 86.705645 iter 30 value 85.875642 iter 40 value 85.434610 iter 50 value 85.335285 iter 60 value 84.320906 iter 70 value 84.161499 iter 80 value 83.870163 iter 90 value 82.082080 iter 100 value 81.336431 final value 81.336431 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 105.746666 iter 10 value 94.226049 iter 20 value 89.275896 iter 30 value 83.646400 iter 40 value 83.014128 iter 50 value 81.866527 iter 60 value 81.405273 iter 70 value 81.050188 iter 80 value 80.898605 iter 90 value 80.692714 iter 100 value 80.666011 final value 80.666011 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 112.175924 iter 10 value 95.324972 iter 20 value 91.316504 iter 30 value 87.709906 iter 40 value 84.467734 iter 50 value 82.742378 iter 60 value 82.549223 iter 70 value 82.363567 iter 80 value 82.350202 iter 90 value 82.072127 iter 100 value 81.262424 final value 81.262424 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.465130 iter 10 value 94.164480 iter 20 value 93.986535 iter 30 value 91.931002 iter 40 value 86.008986 iter 50 value 85.524649 iter 60 value 85.216833 iter 70 value 84.396694 iter 80 value 83.763221 iter 90 value 82.380315 iter 100 value 81.731792 final value 81.731792 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 104.602928 iter 10 value 93.084154 iter 20 value 91.972364 iter 30 value 84.091321 iter 40 value 83.368653 iter 50 value 82.853560 iter 60 value 82.274383 iter 70 value 81.816195 iter 80 value 81.660237 iter 90 value 81.410761 iter 100 value 81.191423 final value 81.191423 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 106.260517 iter 10 value 94.087592 iter 20 value 90.282620 iter 30 value 89.316992 iter 40 value 88.473564 iter 50 value 84.804033 iter 60 value 82.469416 iter 70 value 81.971651 iter 80 value 81.828616 iter 90 value 81.542612 iter 100 value 80.986531 final value 80.986531 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 116.179030 iter 10 value 94.207651 iter 20 value 93.652497 iter 30 value 90.697168 iter 40 value 85.270976 iter 50 value 82.982012 iter 60 value 82.065529 iter 70 value 81.834342 iter 80 value 81.717341 iter 90 value 81.490827 iter 100 value 81.292197 final value 81.292197 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 114.343647 iter 10 value 94.708651 iter 20 value 92.257309 iter 30 value 87.156595 iter 40 value 85.965328 iter 50 value 85.479587 iter 60 value 85.035498 iter 70 value 83.918709 iter 80 value 82.465380 iter 90 value 82.046285 iter 100 value 81.598746 final value 81.598746 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 105.446889 iter 10 value 94.112922 iter 20 value 88.288624 iter 30 value 85.913833 iter 40 value 83.068642 iter 50 value 82.245618 iter 60 value 81.712715 iter 70 value 81.399260 iter 80 value 80.996521 iter 90 value 80.610583 iter 100 value 80.476770 final value 80.476770 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 104.261886 final value 94.054350 converged Fitting Repeat 2 # weights: 103 initial value 109.698646 final value 94.054501 converged Fitting Repeat 3 # weights: 103 initial value 108.384433 iter 10 value 94.076895 iter 20 value 94.073025 iter 30 value 94.052940 final value 94.052914 converged Fitting Repeat 4 # weights: 103 initial value 99.545292 iter 10 value 94.055185 iter 20 value 94.052906 iter 30 value 90.211264 iter 40 value 85.299525 iter 50 value 85.291830 iter 60 value 85.289683 iter 70 value 85.190622 iter 80 value 85.186927 final value 85.186895 converged Fitting Repeat 5 # weights: 103 initial value 96.958335 final value 94.054419 converged Fitting Repeat 1 # weights: 305 initial value 95.055466 iter 10 value 94.057888 iter 20 value 94.052997 iter 30 value 94.048865 iter 40 value 93.915901 iter 50 value 93.902917 iter 60 value 88.091099 iter 70 value 87.091450 iter 80 value 85.731134 iter 90 value 85.522059 iter 100 value 85.513552 final value 85.513552 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 95.621998 iter 10 value 93.995992 iter 20 value 93.925684 final value 93.915984 converged Fitting Repeat 3 # weights: 305 initial value 101.647437 iter 10 value 93.933541 iter 20 value 93.918774 final value 93.918536 converged Fitting Repeat 4 # weights: 305 initial value 95.120887 iter 10 value 93.993455 iter 20 value 93.962553 iter 30 value 93.914206 iter 40 value 86.013549 iter 50 value 85.950954 iter 60 value 85.915943 iter 70 value 84.199994 iter 80 value 83.854286 iter 90 value 83.819413 iter 100 value 83.818269 final value 83.818269 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 107.173834 iter 10 value 94.057725 iter 20 value 91.718352 iter 30 value 85.345620 iter 40 value 85.000584 iter 50 value 83.465745 iter 60 value 80.933132 iter 70 value 80.772150 iter 80 value 80.769877 iter 90 value 80.769770 iter 100 value 80.769703 final value 80.769703 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 96.190897 iter 10 value 93.541278 iter 20 value 93.369192 iter 30 value 93.000433 iter 40 value 86.857151 iter 50 value 85.278447 iter 60 value 84.873087 iter 70 value 84.590543 iter 80 value 84.584722 iter 90 value 83.305519 iter 100 value 83.149162 final value 83.149162 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 106.493412 iter 10 value 94.060916 iter 20 value 93.769449 iter 30 value 85.086704 iter 40 value 85.075814 final value 85.075772 converged Fitting Repeat 3 # weights: 507 initial value 95.429877 iter 10 value 93.924239 iter 20 value 93.916785 iter 30 value 88.175125 iter 40 value 84.588251 iter 50 value 83.606191 iter 60 value 83.022802 iter 70 value 82.732458 iter 80 value 82.547359 iter 90 value 82.407506 iter 100 value 82.403934 final value 82.403934 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 92.155896 iter 10 value 84.947225 iter 20 value 84.359458 iter 30 value 84.322298 iter 40 value 84.218447 iter 50 value 83.844394 iter 60 value 83.709594 iter 70 value 83.692254 iter 80 value 83.691579 iter 90 value 83.690194 iter 100 value 83.686181 final value 83.686181 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 94.921012 final value 94.061211 converged Fitting Repeat 1 # weights: 305 initial value 130.439579 iter 10 value 117.843708 iter 20 value 117.654593 iter 30 value 113.912704 iter 40 value 109.421808 iter 50 value 108.528690 iter 60 value 105.252506 iter 70 value 103.282175 iter 80 value 102.508396 iter 90 value 102.093182 iter 100 value 101.326388 final value 101.326388 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 158.510672 iter 10 value 117.887719 iter 20 value 116.478969 iter 30 value 108.659016 iter 40 value 105.000382 iter 50 value 102.819603 iter 60 value 102.285571 iter 70 value 101.495013 iter 80 value 101.429345 iter 90 value 101.354141 iter 100 value 101.222364 final value 101.222364 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 133.945991 iter 10 value 117.984596 iter 20 value 111.484521 iter 30 value 109.512023 iter 40 value 108.263717 iter 50 value 106.909059 iter 60 value 104.722771 iter 70 value 103.851303 iter 80 value 103.347076 iter 90 value 102.702517 iter 100 value 101.959373 final value 101.959373 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 142.667187 iter 10 value 118.363703 iter 20 value 110.191552 iter 30 value 107.467272 iter 40 value 105.495294 iter 50 value 104.999371 iter 60 value 104.349710 iter 70 value 101.776225 iter 80 value 101.254755 iter 90 value 101.159477 iter 100 value 101.134621 final value 101.134621 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 125.009629 iter 10 value 117.301722 iter 20 value 108.449032 iter 30 value 107.338089 iter 40 value 106.539169 iter 50 value 103.870018 iter 60 value 102.606104 iter 70 value 102.136111 iter 80 value 102.018122 iter 90 value 101.947567 iter 100 value 101.757092 final value 101.757092 stopped after 100 iterations svmRadial ranger Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases RUNIT TEST PROTOCOL -- Tue Oct 18 20:13:17 2022 *********************************************** Number of test functions: 8 Number of errors: 0 Number of failures: 0 1 Test Suite : HPiP RUnit Tests - 8 test functions, 0 errors, 0 failures Number of test functions: 8 Number of errors: 0 Number of failures: 0 Warning messages: 1: The `.data` argument of `add_column()` must have unique names as of tibble 3.0.0. ℹ Use `.name_repair = "minimal"`. ℹ The deprecated feature was likely used in the tibble package. Please report the issue at <https://github.com/tidyverse/tibble/issues>. 2: `repeats` has no meaning for this resampling method. 3: executing %dopar% sequentially: no parallel backend registered > > > > > proc.time() user system elapsed 41.438 3.412 47.709
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 34.413 | 0.984 | 35.398 | |
FreqInteractors | 0.252 | 0.008 | 0.261 | |
calculateAAC | 0.057 | 0.012 | 0.069 | |
calculateAutocor | 0.306 | 0.027 | 0.334 | |
calculateBE | 0.172 | 0.012 | 0.184 | |
calculateCTDC | 0.099 | 0.004 | 0.102 | |
calculateCTDD | 0.757 | 0.024 | 0.781 | |
calculateCTDT | 0.256 | 0.004 | 0.260 | |
calculateCTriad | 0.416 | 0.016 | 0.432 | |
calculateDC | 0.105 | 0.004 | 0.109 | |
calculateF | 0.335 | 0.000 | 0.335 | |
calculateKSAAP | 0.090 | 0.008 | 0.098 | |
calculateQD_Sm | 1.819 | 0.028 | 1.846 | |
calculateTC | 1.807 | 0.192 | 2.000 | |
calculateTC_Sm | 0.294 | 0.012 | 0.305 | |
corr_plot | 35.591 | 0.484 | 36.078 | |
enrichfindP | 0.431 | 0.033 | 11.590 | |
enrichfind_hp | 0.060 | 0.023 | 0.964 | |
enrichplot | 0.236 | 0.016 | 0.252 | |
filter_missing_values | 0.002 | 0.000 | 0.002 | |
getFASTA | 0.126 | 0.004 | 4.466 | |
getHPI | 0.001 | 0.000 | 0.001 | |
get_negativePPI | 0.001 | 0.001 | 0.002 | |
get_positivePPI | 0.000 | 0.001 | 0.000 | |
impute_missing_data | 0.001 | 0.002 | 0.002 | |
plotPPI | 0.062 | 0.004 | 0.065 | |
pred_ensembel | 13.984 | 0.646 | 10.559 | |
var_imp | 33.724 | 0.884 | 34.610 | |