Back to Multiple platform build/check report for BioC 3.19: simplified long |
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This page was generated on 2024-05-04 11:39:21 -0400 (Sat, 04 May 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4753 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" | 4486 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 beta (2024-04-14 r86421) -- "Puppy Cup" | 4519 |
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4479 |
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 |
Package 987/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.10.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | ||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
kjohnson3 | macOS 13.6.5 Ventura / arm64 | see weekly results here | ||||||||||||
To the developers/maintainers of the HPiP package: - 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 Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: HPiP |
Version: 1.10.0 |
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.10.0.tar.gz |
StartedAt: 2024-05-03 22:33:56 -0400 (Fri, 03 May 2024) |
EndedAt: 2024-05-03 22:39:18 -0400 (Fri, 03 May 2024) |
EllapsedTime: 321.7 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.10.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’ * using R version 4.4.0 beta (2024-04-14 r86421) * using platform: x86_64-apple-darwin20 * R was compiled by Apple clang version 14.0.0 (clang-1400.0.29.202) GNU Fortran (GCC) 12.2.0 * running under: macOS Monterey 12.7.1 * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘HPiP/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘HPiP’ version ‘1.10.0’ * 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 ... NOTE License stub is invalid DCF. * checking top-level files ... OK * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking code 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 ... NOTE checkRd: (-1) getHPI.Rd:29: Lost braces 29 | then the Kronecker product is the code{(pm × qn)} block matrix | ^ * 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 var_imp 37.207 2.177 39.941 FSmethod 35.116 1.989 37.567 corr_plot 35.131 1.915 37.405 pred_ensembel 14.793 0.587 11.418 enrichfindP 0.511 0.067 19.623 * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... Running ‘runTests.R’ OK * checking for unstated dependencies in vignettes ... OK * checking package vignettes ... OK * checking running R code from vignettes ... SKIPPED * checking re-building of vignette outputs ... SKIPPED * checking PDF version of manual ... OK * DONE Status: 3 NOTEs See ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’ for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.4-x86_64/Resources/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 4.4.0 beta (2024-04-14 r86421) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 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 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 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 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 96.855511 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 96.909682 iter 10 value 94.443243 iter 10 value 94.443243 iter 10 value 94.443243 final value 94.443243 converged Fitting Repeat 3 # weights: 103 initial value 112.213303 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 102.372338 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 101.506322 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 99.980112 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 100.470463 iter 10 value 92.963394 final value 92.739814 converged Fitting Repeat 3 # weights: 305 initial value 103.634272 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 101.191575 final value 94.443243 converged Fitting Repeat 5 # weights: 305 initial value 106.321938 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 111.891251 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 113.944036 iter 10 value 94.383645 final value 94.383623 converged Fitting Repeat 3 # weights: 507 initial value 96.723619 iter 10 value 94.385077 iter 20 value 93.738875 iter 30 value 91.865316 iter 40 value 91.823484 iter 50 value 91.823082 final value 91.823077 converged Fitting Repeat 4 # weights: 507 initial value 111.005611 final value 94.484210 converged Fitting Repeat 5 # weights: 507 initial value 123.455028 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 99.313264 iter 10 value 94.226852 iter 20 value 88.518569 iter 30 value 88.175064 iter 40 value 86.871640 iter 50 value 84.732570 iter 60 value 84.407348 iter 70 value 84.162653 iter 80 value 84.097895 iter 90 value 84.074229 final value 84.074014 converged Fitting Repeat 2 # weights: 103 initial value 98.285147 iter 10 value 94.453895 iter 20 value 91.323071 iter 30 value 84.568155 iter 40 value 83.595028 iter 50 value 83.213520 iter 60 value 82.774217 iter 70 value 82.669657 final value 82.669432 converged Fitting Repeat 3 # weights: 103 initial value 98.733429 iter 10 value 94.514444 iter 20 value 94.407856 iter 30 value 93.818229 iter 40 value 93.630986 iter 50 value 88.353771 iter 60 value 86.659503 iter 70 value 86.649678 iter 80 value 86.637580 iter 90 value 86.549397 iter 100 value 86.453217 final value 86.453217 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 100.695483 iter 10 value 94.344785 iter 20 value 92.033022 iter 30 value 87.992153 iter 40 value 85.667598 iter 50 value 85.478709 iter 60 value 85.270511 iter 70 value 84.924951 iter 80 value 82.125967 iter 90 value 81.215274 iter 100 value 80.422091 final value 80.422091 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 102.661501 iter 10 value 94.460124 iter 20 value 93.838598 iter 30 value 93.511042 iter 40 value 92.471014 iter 50 value 85.858837 iter 60 value 82.872356 iter 70 value 82.273415 iter 80 value 81.280112 iter 90 value 80.581679 iter 100 value 80.053874 final value 80.053874 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 109.480520 iter 10 value 94.488729 iter 20 value 93.887180 iter 30 value 93.568595 iter 40 value 92.446725 iter 50 value 85.966144 iter 60 value 84.258990 iter 70 value 81.980647 iter 80 value 81.584780 iter 90 value 81.293117 iter 100 value 80.355458 final value 80.355458 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 101.682103 iter 10 value 94.440418 iter 20 value 87.936615 iter 30 value 85.028600 iter 40 value 83.803623 iter 50 value 83.453119 iter 60 value 82.004506 iter 70 value 80.849111 iter 80 value 80.522681 iter 90 value 80.333042 iter 100 value 80.249678 final value 80.249678 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 109.692561 iter 10 value 94.808793 iter 20 value 93.246484 iter 30 value 84.551945 iter 40 value 84.301601 iter 50 value 81.074243 iter 60 value 79.415680 iter 70 value 78.690062 iter 80 value 78.488650 iter 90 value 78.378946 iter 100 value 78.226972 final value 78.226972 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 101.923445 iter 10 value 94.026313 iter 20 value 85.717926 iter 30 value 84.171040 iter 40 value 83.440537 iter 50 value 82.131607 iter 60 value 79.361299 iter 70 value 78.654230 iter 80 value 78.331198 iter 90 value 78.234318 iter 100 value 78.216885 final value 78.216885 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 102.717153 iter 10 value 94.359031 iter 20 value 93.767992 iter 30 value 86.814071 iter 40 value 85.406989 iter 50 value 83.908358 iter 60 value 83.465182 iter 70 value 82.913771 iter 80 value 81.912703 iter 90 value 80.621512 iter 100 value 79.714470 final value 79.714470 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 104.898031 iter 10 value 94.347048 iter 20 value 84.726732 iter 30 value 83.728244 iter 40 value 83.053995 iter 50 value 82.228556 iter 60 value 81.549919 iter 70 value 80.810417 iter 80 value 80.277985 iter 90 value 79.565251 iter 100 value 78.781151 final value 78.781151 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 123.838796 iter 10 value 94.567175 iter 20 value 91.937127 iter 30 value 88.316431 iter 40 value 84.578003 iter 50 value 83.435011 iter 60 value 82.946420 iter 70 value 81.206387 iter 80 value 80.400538 iter 90 value 79.567542 iter 100 value 78.929063 final value 78.929063 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 106.802547 iter 10 value 94.582991 iter 20 value 92.772204 iter 30 value 85.461235 iter 40 value 82.486338 iter 50 value 81.578915 iter 60 value 80.063801 iter 70 value 79.066205 iter 80 value 78.825748 iter 90 value 78.786531 iter 100 value 78.588795 final value 78.588795 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 110.005385 iter 10 value 94.205407 iter 20 value 86.853411 iter 30 value 86.082706 iter 40 value 84.792484 iter 50 value 82.194520 iter 60 value 81.381317 iter 70 value 79.687262 iter 80 value 78.689737 iter 90 value 78.188126 iter 100 value 78.009368 final value 78.009368 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 103.547117 iter 10 value 91.677255 iter 20 value 83.265343 iter 30 value 81.134443 iter 40 value 80.484064 iter 50 value 80.242073 iter 60 value 80.046781 iter 70 value 78.772610 iter 80 value 78.268002 iter 90 value 78.137379 iter 100 value 78.095982 final value 78.095982 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 100.120949 final value 94.485730 converged Fitting Repeat 2 # weights: 103 initial value 103.353628 final value 94.444642 converged Fitting Repeat 3 # weights: 103 initial value 115.181073 iter 10 value 94.489015 final value 94.487279 converged Fitting Repeat 4 # weights: 103 initial value 97.938675 iter 10 value 94.485781 iter 20 value 94.484215 final value 94.484209 converged Fitting Repeat 5 # weights: 103 initial value 108.604986 iter 10 value 94.444964 iter 20 value 93.160083 iter 30 value 88.214626 iter 40 value 85.934600 iter 50 value 85.358481 final value 85.355433 converged Fitting Repeat 1 # weights: 305 initial value 102.458060 iter 10 value 94.489395 iter 20 value 94.484346 final value 94.484237 converged Fitting Repeat 2 # weights: 305 initial value 110.042339 iter 10 value 94.488920 iter 20 value 94.484356 iter 30 value 94.484160 iter 40 value 93.688530 final value 93.688493 converged Fitting Repeat 3 # weights: 305 initial value 108.419279 iter 10 value 93.693508 iter 20 value 93.542876 iter 30 value 93.301445 iter 40 value 93.300200 final value 93.300155 converged Fitting Repeat 4 # weights: 305 initial value 95.029885 iter 10 value 94.433728 iter 20 value 90.352446 iter 30 value 89.075130 iter 40 value 85.136364 iter 50 value 83.959076 iter 60 value 82.931889 iter 70 value 82.521886 iter 80 value 80.629949 iter 90 value 78.190049 iter 100 value 77.818205 final value 77.818205 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 94.677918 iter 10 value 94.489548 iter 20 value 94.400475 iter 30 value 92.259606 iter 40 value 92.210168 final value 92.209947 converged Fitting Repeat 1 # weights: 507 initial value 107.036335 iter 10 value 94.492147 iter 20 value 94.484801 iter 30 value 93.921475 iter 40 value 93.688551 final value 93.688541 converged Fitting Repeat 2 # weights: 507 initial value 98.117817 iter 10 value 93.941905 iter 20 value 92.741490 iter 30 value 92.738380 iter 40 value 89.777009 iter 50 value 89.388373 iter 60 value 89.379734 iter 70 value 89.378564 iter 80 value 89.376627 iter 90 value 88.203447 iter 100 value 80.021232 final value 80.021232 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 105.698775 iter 10 value 94.451478 iter 20 value 94.002516 iter 30 value 86.652088 iter 40 value 83.342566 iter 50 value 83.340751 iter 60 value 83.123508 final value 83.119220 converged Fitting Repeat 4 # weights: 507 initial value 118.811028 iter 10 value 94.451887 iter 20 value 94.443860 final value 94.443394 converged Fitting Repeat 5 # weights: 507 initial value 96.410115 iter 10 value 93.305661 iter 20 value 92.700999 final value 92.700570 converged Fitting Repeat 1 # weights: 103 initial value 94.680452 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 99.162929 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 103.953083 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 114.880951 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 95.836701 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 98.281058 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 95.933611 iter 10 value 93.231692 iter 20 value 93.225338 final value 93.225316 converged Fitting Repeat 3 # weights: 305 initial value 96.971343 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 96.544160 iter 10 value 91.911309 iter 20 value 90.155258 iter 20 value 90.155258 iter 30 value 90.140509 final value 90.140459 converged Fitting Repeat 5 # weights: 305 initial value 95.227844 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 107.839799 iter 10 value 92.748925 final value 92.706753 converged Fitting Repeat 2 # weights: 507 initial value 105.857713 final value 93.582418 converged Fitting Repeat 3 # weights: 507 initial value 98.258900 final value 93.457887 converged Fitting Repeat 4 # weights: 507 initial value 101.613731 iter 10 value 93.582419 iter 10 value 93.582418 iter 10 value 93.582418 final value 93.582418 converged Fitting Repeat 5 # weights: 507 initial value 115.500858 iter 10 value 93.457889 final value 93.457887 converged Fitting Repeat 1 # weights: 103 initial value 101.005931 iter 10 value 94.026792 iter 20 value 88.603761 iter 30 value 87.760304 iter 40 value 87.367955 iter 50 value 86.856847 iter 60 value 84.671194 iter 70 value 84.075109 iter 80 value 84.014804 final value 84.014760 converged Fitting Repeat 2 # weights: 103 initial value 98.805794 iter 10 value 93.627400 iter 20 value 86.385827 iter 30 value 84.719005 iter 40 value 84.370959 iter 50 value 84.014946 iter 60 value 83.522041 iter 70 value 83.391896 final value 83.391457 converged Fitting Repeat 3 # weights: 103 initial value 96.325299 iter 10 value 94.117695 iter 20 value 94.056391 iter 30 value 93.834514 iter 40 value 93.684798 iter 50 value 93.427798 iter 60 value 84.972714 iter 70 value 83.808838 iter 80 value 82.856978 iter 90 value 82.076195 iter 100 value 81.709012 final value 81.709012 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 105.359563 iter 10 value 94.844362 iter 20 value 94.056856 iter 30 value 93.987206 iter 40 value 93.851931 iter 50 value 93.749554 iter 60 value 84.855538 iter 70 value 84.049669 iter 80 value 83.169728 iter 90 value 82.708664 iter 100 value 82.619916 final value 82.619916 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 99.042451 iter 10 value 93.824878 iter 20 value 85.180189 iter 30 value 84.498524 iter 40 value 84.252395 iter 50 value 83.903508 iter 60 value 82.812495 iter 70 value 82.704880 iter 80 value 82.673761 final value 82.673753 converged Fitting Repeat 1 # weights: 305 initial value 108.414414 iter 10 value 94.085960 iter 20 value 86.029085 iter 30 value 84.671758 iter 40 value 83.628473 iter 50 value 82.741410 iter 60 value 81.884660 iter 70 value 81.494048 iter 80 value 80.958162 iter 90 value 80.629771 iter 100 value 80.533592 final value 80.533592 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 116.472329 iter 10 value 93.833917 iter 20 value 91.292879 iter 30 value 87.079881 iter 40 value 86.068395 iter 50 value 82.731932 iter 60 value 81.253468 iter 70 value 81.144023 iter 80 value 80.985774 iter 90 value 80.947913 iter 100 value 80.933016 final value 80.933016 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 106.161210 iter 10 value 94.931349 iter 20 value 85.366435 iter 30 value 84.536939 iter 40 value 83.100189 iter 50 value 82.616009 iter 60 value 82.463060 iter 70 value 81.656531 iter 80 value 81.646892 iter 90 value 81.599824 iter 100 value 81.191936 final value 81.191936 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 114.126963 iter 10 value 93.698298 iter 20 value 87.733735 iter 30 value 87.305193 iter 40 value 86.047827 iter 50 value 81.711894 iter 60 value 81.253825 iter 70 value 81.131566 iter 80 value 81.040060 iter 90 value 80.652288 iter 100 value 80.484007 final value 80.484007 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 107.181083 iter 10 value 94.045097 iter 20 value 90.569563 iter 30 value 86.055601 iter 40 value 85.076268 iter 50 value 83.267467 iter 60 value 82.760537 iter 70 value 82.394143 iter 80 value 82.226811 iter 90 value 82.191087 iter 100 value 81.458802 final value 81.458802 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 104.821195 iter 10 value 94.401165 iter 20 value 91.930427 iter 30 value 85.212592 iter 40 value 84.363964 iter 50 value 83.001446 iter 60 value 81.799179 iter 70 value 81.611409 iter 80 value 81.437287 iter 90 value 81.224943 iter 100 value 80.945036 final value 80.945036 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 140.972801 iter 10 value 93.983165 iter 20 value 88.643258 iter 30 value 86.002961 iter 40 value 85.243043 iter 50 value 85.006895 iter 60 value 84.264165 iter 70 value 82.594209 iter 80 value 81.872515 iter 90 value 81.507585 iter 100 value 81.381402 final value 81.381402 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 104.884891 iter 10 value 86.711937 iter 20 value 85.311933 iter 30 value 83.882999 iter 40 value 83.661534 iter 50 value 83.520889 iter 60 value 82.689741 iter 70 value 82.169728 iter 80 value 81.844501 iter 90 value 81.653545 iter 100 value 81.414504 final value 81.414504 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 123.050948 iter 10 value 94.952968 iter 20 value 94.259077 iter 30 value 93.516804 iter 40 value 86.518280 iter 50 value 84.582439 iter 60 value 84.251369 iter 70 value 83.004674 iter 80 value 81.132413 iter 90 value 80.807354 iter 100 value 80.340087 final value 80.340087 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 137.337401 iter 10 value 93.320526 iter 20 value 85.982833 iter 30 value 84.245080 iter 40 value 83.647479 iter 50 value 83.080500 iter 60 value 82.661965 iter 70 value 81.764217 iter 80 value 80.827378 iter 90 value 80.610381 iter 100 value 80.537958 final value 80.537958 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.398437 final value 94.054585 converged Fitting Repeat 2 # weights: 103 initial value 97.284079 iter 10 value 93.941872 iter 20 value 93.584266 iter 30 value 93.583232 final value 93.583217 converged Fitting Repeat 3 # weights: 103 initial value 102.724149 final value 94.036595 converged Fitting Repeat 4 # weights: 103 initial value 102.892460 final value 94.054609 converged Fitting Repeat 5 # weights: 103 initial value 99.615692 iter 10 value 94.054278 iter 20 value 94.052928 final value 94.052923 converged Fitting Repeat 1 # weights: 305 initial value 99.114809 iter 10 value 93.587703 iter 20 value 93.013932 iter 30 value 85.245042 iter 40 value 84.055365 iter 50 value 83.059025 iter 60 value 83.042051 iter 70 value 83.016811 iter 80 value 83.016414 iter 90 value 82.963341 iter 100 value 82.868089 final value 82.868089 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 109.089892 iter 10 value 93.587245 iter 20 value 93.583840 iter 30 value 93.334286 iter 40 value 84.910019 iter 50 value 84.641775 iter 60 value 84.637724 iter 70 value 84.418069 iter 80 value 84.404083 iter 90 value 84.217097 iter 100 value 83.080634 final value 83.080634 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 98.358968 iter 10 value 93.840934 iter 20 value 93.837418 iter 30 value 93.440598 iter 40 value 93.344135 final value 93.342325 converged Fitting Repeat 4 # weights: 305 initial value 94.626706 iter 10 value 94.057823 iter 20 value 93.758738 iter 30 value 86.433153 iter 40 value 84.546715 iter 50 value 83.949580 iter 60 value 82.395780 iter 70 value 82.014093 iter 80 value 82.013241 final value 82.012597 converged Fitting Repeat 5 # weights: 305 initial value 99.783827 iter 10 value 90.421732 iter 20 value 87.418658 iter 30 value 87.202605 iter 40 value 87.166624 iter 50 value 87.165083 iter 60 value 87.161525 iter 70 value 87.156174 iter 80 value 87.155964 iter 90 value 82.982411 iter 100 value 82.395570 final value 82.395570 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 95.634520 iter 10 value 93.912434 iter 20 value 87.453499 iter 30 value 83.609584 iter 40 value 82.294134 iter 50 value 82.146530 iter 60 value 81.526689 iter 70 value 81.371353 iter 80 value 81.351949 final value 81.351907 converged Fitting Repeat 2 # weights: 507 initial value 111.347401 iter 10 value 94.059794 iter 20 value 94.047610 iter 30 value 93.358899 iter 40 value 91.191675 iter 50 value 90.264042 iter 60 value 90.263641 iter 70 value 90.017107 iter 80 value 83.511863 iter 90 value 82.866317 iter 100 value 82.858660 final value 82.858660 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 102.884158 iter 10 value 88.563829 iter 20 value 88.507541 iter 30 value 86.393778 iter 40 value 86.390282 iter 50 value 83.224376 iter 60 value 80.858430 iter 70 value 80.234942 iter 80 value 80.023140 iter 90 value 79.983435 iter 100 value 79.814273 final value 79.814273 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 97.383935 iter 10 value 93.590244 iter 20 value 93.584372 iter 30 value 93.569145 final value 93.568593 converged Fitting Repeat 5 # weights: 507 initial value 110.795055 iter 10 value 94.061047 iter 20 value 94.052177 iter 30 value 92.446756 iter 40 value 88.050002 iter 50 value 88.047714 iter 60 value 88.044575 iter 70 value 88.043304 iter 80 value 87.951911 iter 90 value 87.260482 iter 100 value 83.128473 final value 83.128473 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 109.207109 iter 10 value 93.109891 final value 93.109890 converged Fitting Repeat 2 # weights: 103 initial value 96.629282 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 98.209718 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 97.476319 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 106.056300 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 114.861219 iter 10 value 94.466823 iter 10 value 94.466823 iter 10 value 94.466823 final value 94.466823 converged Fitting Repeat 2 # weights: 305 initial value 94.429124 iter 10 value 93.110246 final value 93.109891 converged Fitting Repeat 3 # weights: 305 initial value 94.754598 iter 10 value 94.479296 final value 94.466823 converged Fitting Repeat 4 # weights: 305 initial value 95.241875 final value 94.466823 converged Fitting Repeat 5 # weights: 305 initial value 100.201159 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 105.976257 final value 94.466823 converged Fitting Repeat 2 # weights: 507 initial value 108.079263 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 95.599487 iter 10 value 93.109892 final value 93.109890 converged Fitting Repeat 4 # weights: 507 initial value 98.679573 final value 94.466823 converged Fitting Repeat 5 # weights: 507 initial value 107.649436 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 103.930227 iter 10 value 94.327592 iter 20 value 88.996572 iter 30 value 85.948664 iter 40 value 83.237410 iter 50 value 83.031062 iter 60 value 83.019008 iter 70 value 82.953732 iter 80 value 82.931835 final value 82.931783 converged Fitting Repeat 2 # weights: 103 initial value 97.070458 iter 10 value 94.264255 iter 20 value 86.287606 iter 30 value 84.433875 iter 40 value 83.716470 iter 50 value 83.575764 iter 60 value 83.183015 iter 70 value 83.001071 iter 80 value 82.946228 iter 90 value 82.932197 final value 82.931783 converged Fitting Repeat 3 # weights: 103 initial value 104.310935 iter 10 value 94.470231 iter 20 value 90.569406 iter 30 value 84.722655 iter 40 value 81.397331 iter 50 value 81.289351 iter 60 value 80.705391 iter 70 value 79.966253 iter 80 value 79.801201 iter 90 value 79.621976 iter 100 value 79.279704 final value 79.279704 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 102.906947 iter 10 value 94.488769 iter 20 value 93.963427 iter 30 value 86.994251 iter 40 value 83.881125 iter 50 value 83.385075 iter 60 value 83.060862 iter 70 value 83.003794 iter 70 value 83.003793 iter 70 value 83.003793 final value 83.003793 converged Fitting Repeat 5 # weights: 103 initial value 96.366871 iter 10 value 94.397276 iter 20 value 88.063349 iter 30 value 85.676794 iter 40 value 85.464487 iter 50 value 82.911996 iter 60 value 82.629054 iter 70 value 82.626623 final value 82.626622 converged Fitting Repeat 1 # weights: 305 initial value 117.572350 iter 10 value 94.429270 iter 20 value 85.327105 iter 30 value 83.695401 iter 40 value 83.242622 iter 50 value 83.028620 iter 60 value 83.005677 iter 70 value 82.912343 iter 80 value 82.798422 iter 90 value 82.742267 iter 100 value 82.518600 final value 82.518600 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 114.204873 iter 10 value 94.523164 iter 20 value 89.099402 iter 30 value 88.604426 iter 40 value 87.134194 iter 50 value 84.052891 iter 60 value 83.262259 iter 70 value 82.814863 iter 80 value 82.697780 iter 90 value 82.480485 iter 100 value 81.371233 final value 81.371233 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 110.626429 iter 10 value 94.471319 iter 20 value 92.210702 iter 30 value 82.181533 iter 40 value 80.469827 iter 50 value 79.708863 iter 60 value 79.169453 iter 70 value 79.067281 iter 80 value 79.064674 iter 90 value 79.055618 iter 100 value 78.822431 final value 78.822431 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 101.159647 iter 10 value 94.546826 iter 20 value 94.425089 iter 30 value 86.416161 iter 40 value 81.209738 iter 50 value 80.592744 iter 60 value 78.605382 iter 70 value 78.279562 iter 80 value 78.205795 iter 90 value 78.168744 iter 100 value 78.130628 final value 78.130628 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 107.404210 iter 10 value 94.093457 iter 20 value 86.777527 iter 30 value 85.561912 iter 40 value 85.234952 iter 50 value 82.883547 iter 60 value 80.986222 iter 70 value 80.856489 iter 80 value 80.760401 iter 90 value 80.681931 iter 100 value 80.621991 final value 80.621991 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 152.541947 iter 10 value 101.817404 iter 20 value 92.668688 iter 30 value 87.894102 iter 40 value 86.068967 iter 50 value 83.158129 iter 60 value 79.594009 iter 70 value 79.030442 iter 80 value 78.440398 iter 90 value 78.233663 iter 100 value 77.995049 final value 77.995049 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 112.010322 iter 10 value 94.664715 iter 20 value 84.568503 iter 30 value 80.788514 iter 40 value 80.309749 iter 50 value 79.813531 iter 60 value 78.576410 iter 70 value 78.208624 iter 80 value 77.843522 iter 90 value 77.510977 iter 100 value 77.412471 final value 77.412471 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 106.990153 iter 10 value 92.888240 iter 20 value 85.552997 iter 30 value 84.115090 iter 40 value 82.628626 iter 50 value 79.707709 iter 60 value 79.068350 iter 70 value 78.867298 iter 80 value 78.717161 iter 90 value 78.249941 iter 100 value 78.024421 final value 78.024421 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 128.057604 iter 10 value 94.701020 iter 20 value 94.309713 iter 30 value 83.530805 iter 40 value 82.810219 iter 50 value 80.478052 iter 60 value 78.344963 iter 70 value 77.905995 iter 80 value 77.722809 iter 90 value 77.652481 iter 100 value 77.628963 final value 77.628963 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 103.770518 iter 10 value 92.524880 iter 20 value 83.801707 iter 30 value 82.497721 iter 40 value 81.643490 iter 50 value 80.032704 iter 60 value 79.480099 iter 70 value 78.450239 iter 80 value 78.006705 iter 90 value 77.860393 iter 100 value 77.690505 final value 77.690505 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.905536 final value 94.486007 converged Fitting Repeat 2 # weights: 103 initial value 99.897714 iter 10 value 94.485726 iter 20 value 94.484228 final value 94.484220 converged Fitting Repeat 3 # weights: 103 initial value 99.977466 iter 10 value 94.485685 iter 20 value 94.375108 iter 30 value 91.391102 iter 40 value 91.387718 final value 91.387698 converged Fitting Repeat 4 # weights: 103 initial value 105.205446 final value 94.486207 converged Fitting Repeat 5 # weights: 103 initial value 98.992711 final value 94.485835 converged Fitting Repeat 1 # weights: 305 initial value 101.177639 iter 10 value 93.731295 iter 20 value 92.871117 iter 30 value 92.865693 iter 40 value 92.634537 iter 50 value 86.586537 iter 60 value 84.147095 iter 70 value 83.924767 iter 80 value 83.889768 iter 90 value 83.889505 iter 100 value 83.888407 final value 83.888407 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 98.497332 iter 10 value 94.488982 iter 20 value 93.678975 iter 30 value 82.802149 iter 40 value 82.781487 final value 82.781189 converged Fitting Repeat 3 # weights: 305 initial value 99.200671 iter 10 value 94.315321 iter 20 value 93.367596 iter 30 value 82.838363 iter 40 value 82.658743 iter 50 value 82.655699 iter 60 value 82.650546 iter 70 value 82.298467 iter 80 value 82.092110 iter 90 value 82.091122 iter 100 value 81.511989 final value 81.511989 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 99.670177 iter 10 value 94.489213 iter 20 value 94.352075 iter 30 value 90.348455 iter 40 value 84.442479 iter 50 value 84.278849 iter 60 value 84.274218 iter 70 value 82.372084 iter 80 value 82.226692 final value 82.225588 converged Fitting Repeat 5 # weights: 305 initial value 95.169341 iter 10 value 94.488708 iter 20 value 94.368378 iter 30 value 83.147179 iter 40 value 82.484914 iter 50 value 82.415962 iter 60 value 81.936400 iter 70 value 80.415690 iter 80 value 80.411868 iter 90 value 80.406348 iter 100 value 79.985133 final value 79.985133 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 118.515711 iter 10 value 94.475261 iter 20 value 94.468154 iter 30 value 91.703647 iter 40 value 85.653936 iter 50 value 84.524288 iter 60 value 84.511044 iter 70 value 84.008005 iter 80 value 83.877051 iter 90 value 80.104372 iter 100 value 78.508909 final value 78.508909 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 151.712489 iter 10 value 94.493754 iter 20 value 94.486106 iter 30 value 88.461236 iter 40 value 82.945753 iter 50 value 82.654730 iter 60 value 82.653980 iter 70 value 82.651589 iter 80 value 82.600341 iter 90 value 82.112010 iter 100 value 81.555150 final value 81.555150 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 108.468193 iter 10 value 94.474864 iter 20 value 94.307779 final value 94.306457 converged Fitting Repeat 4 # weights: 507 initial value 109.883674 iter 10 value 91.133496 iter 20 value 90.734038 iter 30 value 90.730007 iter 40 value 90.729015 iter 50 value 90.727225 iter 60 value 89.918247 iter 70 value 81.936653 iter 80 value 81.283326 iter 90 value 81.140815 iter 100 value 81.119956 final value 81.119956 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 107.142938 iter 10 value 92.368779 iter 20 value 91.886534 iter 30 value 88.844077 iter 40 value 82.216509 iter 50 value 79.565196 iter 60 value 77.797815 iter 70 value 77.676573 iter 80 value 77.620952 iter 90 value 77.567436 iter 100 value 77.564945 final value 77.564945 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.419121 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 94.588201 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 95.500607 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 95.698582 final value 94.484207 converged Fitting Repeat 5 # weights: 103 initial value 94.674210 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 98.080942 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 112.723090 iter 10 value 94.427726 iter 10 value 94.427726 iter 10 value 94.427726 final value 94.427726 converged Fitting Repeat 3 # weights: 305 initial value 103.803956 final value 94.427725 converged Fitting Repeat 4 # weights: 305 initial value 101.339211 final value 94.466823 converged Fitting Repeat 5 # weights: 305 initial value 111.252527 final value 94.466823 converged Fitting Repeat 1 # weights: 507 initial value 108.252398 final value 94.448052 converged Fitting Repeat 2 # weights: 507 initial value 112.202683 iter 10 value 94.424733 final value 94.424077 converged Fitting Repeat 3 # weights: 507 initial value 105.846814 final value 94.427726 converged Fitting Repeat 4 # weights: 507 initial value 95.252515 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 99.890687 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 106.599050 iter 10 value 94.488543 iter 20 value 94.431295 iter 30 value 92.420309 iter 40 value 91.598889 iter 50 value 85.917379 iter 60 value 85.672228 iter 70 value 85.503925 iter 80 value 85.208610 iter 90 value 85.135080 iter 100 value 85.101371 final value 85.101371 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 105.325931 iter 10 value 94.255726 iter 20 value 90.912442 iter 30 value 88.187004 iter 40 value 86.704435 iter 50 value 86.557198 iter 60 value 86.302991 iter 70 value 84.671029 iter 80 value 83.960042 iter 90 value 83.854625 final value 83.854462 converged Fitting Repeat 3 # weights: 103 initial value 96.623896 iter 10 value 94.486419 iter 20 value 93.973898 iter 30 value 89.938966 iter 40 value 87.865514 iter 50 value 87.560785 iter 60 value 86.900696 iter 70 value 86.366300 iter 80 value 84.485487 iter 90 value 84.167941 iter 100 value 83.998927 final value 83.998927 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 105.801533 iter 10 value 94.483479 iter 20 value 94.419574 iter 30 value 94.414416 iter 40 value 94.348575 iter 50 value 87.347600 iter 60 value 86.814194 iter 70 value 86.686505 iter 80 value 86.273503 iter 90 value 84.681065 iter 100 value 84.285258 final value 84.285258 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 96.937616 iter 10 value 94.461377 iter 20 value 89.451805 iter 30 value 86.553538 iter 40 value 84.559024 iter 50 value 84.450312 iter 60 value 84.213272 iter 70 value 84.035020 iter 80 value 83.873904 iter 90 value 83.701907 final value 83.697907 converged Fitting Repeat 1 # weights: 305 initial value 103.144159 iter 10 value 94.063286 iter 20 value 88.509706 iter 30 value 87.523057 iter 40 value 87.363160 iter 50 value 87.048769 iter 60 value 86.444767 iter 70 value 83.652656 iter 80 value 83.243228 iter 90 value 82.756728 iter 100 value 82.730575 final value 82.730575 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 101.504390 iter 10 value 94.386646 iter 20 value 88.655055 iter 30 value 87.514587 iter 40 value 85.048464 iter 50 value 84.221310 iter 60 value 84.091829 iter 70 value 83.934590 iter 80 value 83.627217 iter 90 value 83.498990 iter 100 value 83.434311 final value 83.434311 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 106.172114 iter 10 value 97.928942 iter 20 value 95.871102 iter 30 value 94.489145 iter 40 value 94.406353 iter 50 value 93.598846 iter 60 value 87.595925 iter 70 value 87.178621 iter 80 value 86.618794 iter 90 value 85.198615 iter 100 value 84.400876 final value 84.400876 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 104.906075 iter 10 value 94.507089 iter 20 value 93.178798 iter 30 value 89.284760 iter 40 value 88.365771 iter 50 value 87.915609 iter 60 value 87.386783 iter 70 value 87.022852 iter 80 value 86.962774 iter 90 value 86.548070 iter 100 value 84.045944 final value 84.045944 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 106.218245 iter 10 value 94.504894 iter 20 value 94.400217 iter 30 value 93.312028 iter 40 value 92.925643 iter 50 value 87.730934 iter 60 value 86.021037 iter 70 value 85.697575 iter 80 value 85.563223 iter 90 value 83.684943 iter 100 value 82.954352 final value 82.954352 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 115.727699 iter 10 value 96.024676 iter 20 value 94.455775 iter 30 value 92.405499 iter 40 value 85.638090 iter 50 value 84.991367 iter 60 value 84.918143 iter 70 value 84.685177 iter 80 value 84.169422 iter 90 value 83.909660 iter 100 value 83.608542 final value 83.608542 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 108.190800 iter 10 value 94.505543 iter 20 value 90.882497 iter 30 value 88.671245 iter 40 value 87.050875 iter 50 value 85.196763 iter 60 value 84.729058 iter 70 value 84.601014 iter 80 value 84.211292 iter 90 value 83.504598 iter 100 value 83.069318 final value 83.069318 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 112.163948 iter 10 value 94.510653 iter 20 value 92.232017 iter 30 value 90.083789 iter 40 value 87.300430 iter 50 value 87.116401 iter 60 value 85.333002 iter 70 value 84.909633 iter 80 value 84.878352 iter 90 value 84.847009 iter 100 value 84.729545 final value 84.729545 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 103.380387 iter 10 value 94.991184 iter 20 value 94.430635 iter 30 value 89.830522 iter 40 value 88.833308 iter 50 value 87.644583 iter 60 value 86.152814 iter 70 value 85.301871 iter 80 value 84.903855 iter 90 value 84.583646 iter 100 value 83.871934 final value 83.871934 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 104.455009 iter 10 value 94.512844 iter 20 value 94.194256 iter 30 value 87.958043 iter 40 value 86.589537 iter 50 value 85.411828 iter 60 value 84.458537 iter 70 value 83.557947 iter 80 value 83.130554 iter 90 value 82.859665 iter 100 value 82.484731 final value 82.484731 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.161561 final value 94.486053 converged Fitting Repeat 2 # weights: 103 initial value 96.349875 final value 94.430569 converged Fitting Repeat 3 # weights: 103 initial value 105.976450 final value 94.486006 converged Fitting Repeat 4 # weights: 103 initial value 107.968515 iter 10 value 94.468593 iter 20 value 94.443843 iter 30 value 94.385809 final value 94.385714 converged Fitting Repeat 5 # weights: 103 initial value 106.801228 iter 10 value 94.485832 iter 20 value 94.484270 final value 94.484215 converged Fitting Repeat 1 # weights: 305 initial value 102.870410 iter 10 value 94.489289 iter 20 value 94.484251 iter 30 value 90.682041 final value 90.352772 converged Fitting Repeat 2 # weights: 305 initial value 106.765390 iter 10 value 94.488949 iter 20 value 94.454334 iter 30 value 85.864114 iter 40 value 85.839480 iter 50 value 85.838689 iter 50 value 85.838689 iter 50 value 85.838689 final value 85.838689 converged Fitting Repeat 3 # weights: 305 initial value 98.277531 iter 10 value 94.432901 iter 20 value 94.412889 iter 30 value 89.080731 iter 40 value 87.459101 iter 50 value 85.956071 iter 60 value 85.404385 iter 70 value 85.182875 final value 85.173104 converged Fitting Repeat 4 # weights: 305 initial value 97.647038 iter 10 value 94.471900 iter 20 value 94.459103 iter 30 value 92.015525 iter 40 value 87.898798 iter 50 value 87.864578 iter 60 value 87.841126 iter 70 value 87.793919 iter 80 value 87.778061 iter 90 value 87.777422 final value 87.777412 converged Fitting Repeat 5 # weights: 305 initial value 107.821974 iter 10 value 94.471433 iter 20 value 94.428196 iter 30 value 87.559678 iter 40 value 84.485934 iter 50 value 82.286523 iter 60 value 81.485724 iter 70 value 80.807458 iter 80 value 80.770309 iter 90 value 80.770265 final value 80.769724 converged Fitting Repeat 1 # weights: 507 initial value 106.923719 iter 10 value 94.492266 iter 20 value 94.486963 iter 30 value 94.455109 iter 40 value 94.452656 iter 50 value 92.526064 iter 60 value 87.294342 iter 70 value 87.294100 iter 80 value 85.910382 iter 90 value 85.509621 iter 100 value 85.479491 final value 85.479491 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 101.520523 iter 10 value 94.489061 iter 20 value 94.467639 final value 94.467300 converged Fitting Repeat 3 # weights: 507 initial value 98.003048 iter 10 value 93.982874 iter 20 value 93.850554 iter 30 value 90.201637 iter 40 value 90.068665 final value 90.047633 converged Fitting Repeat 4 # weights: 507 initial value 108.339334 iter 10 value 94.492498 iter 20 value 94.483860 iter 30 value 93.761400 iter 40 value 91.286743 iter 50 value 91.067566 iter 60 value 91.056966 iter 70 value 86.979392 iter 80 value 86.969059 iter 90 value 86.961219 iter 100 value 86.354432 final value 86.354432 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 96.642670 iter 10 value 94.469960 iter 20 value 94.440623 iter 30 value 89.042893 iter 40 value 87.813567 final value 87.811288 converged Fitting Repeat 1 # weights: 103 initial value 99.464694 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 96.355715 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 106.139483 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 103.572445 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 94.125755 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 96.860601 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 98.118972 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 96.471843 final value 93.836065 converged Fitting Repeat 4 # weights: 305 initial value 100.475884 final value 93.836066 converged Fitting Repeat 5 # weights: 305 initial value 115.723612 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 139.939412 iter 10 value 93.864568 final value 93.860355 converged Fitting Repeat 2 # weights: 507 initial value 103.307579 iter 10 value 92.395593 iter 20 value 87.254422 final value 87.247250 converged Fitting Repeat 3 # weights: 507 initial value 103.101751 final value 94.011561 converged Fitting Repeat 4 # weights: 507 initial value 101.619511 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 99.065951 iter 10 value 83.014717 iter 20 value 82.658536 iter 30 value 82.543227 iter 40 value 82.541236 iter 50 value 82.540439 final value 82.540430 converged Fitting Repeat 1 # weights: 103 initial value 97.659862 iter 10 value 93.772358 iter 20 value 88.611703 iter 30 value 87.636629 iter 40 value 86.745046 iter 50 value 85.967046 iter 60 value 85.453818 iter 70 value 85.255171 iter 80 value 85.235249 final value 85.234283 converged Fitting Repeat 2 # weights: 103 initial value 95.733636 iter 10 value 94.056982 iter 20 value 93.960552 iter 30 value 93.854553 iter 40 value 93.842310 iter 50 value 93.840251 iter 60 value 93.839149 iter 60 value 93.839149 final value 93.839149 converged Fitting Repeat 3 # weights: 103 initial value 99.491704 iter 10 value 94.064975 iter 20 value 92.412380 iter 30 value 90.670634 iter 40 value 90.548048 iter 50 value 89.189037 iter 60 value 86.817439 iter 70 value 83.650868 iter 80 value 83.114740 iter 90 value 82.985096 iter 100 value 82.775806 final value 82.775806 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 95.989231 iter 10 value 93.988102 iter 20 value 93.889877 iter 30 value 93.708537 iter 40 value 92.676272 iter 50 value 86.338051 iter 60 value 85.478019 iter 70 value 84.891086 iter 80 value 83.739602 iter 90 value 83.275702 iter 100 value 82.866190 final value 82.866190 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 96.488264 iter 10 value 93.841161 iter 20 value 89.849272 iter 30 value 88.375085 iter 40 value 87.474089 iter 50 value 86.727430 iter 60 value 86.620298 final value 86.620260 converged Fitting Repeat 1 # weights: 305 initial value 106.797172 iter 10 value 93.997148 iter 20 value 87.661896 iter 30 value 86.837773 iter 40 value 86.233266 iter 50 value 84.717842 iter 60 value 82.667254 iter 70 value 82.347014 iter 80 value 81.929739 iter 90 value 81.514344 iter 100 value 80.829731 final value 80.829731 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 109.576834 iter 10 value 93.983132 iter 20 value 90.877291 iter 30 value 87.758771 iter 40 value 83.731961 iter 50 value 82.988174 iter 60 value 82.817051 iter 70 value 82.060764 iter 80 value 81.318520 iter 90 value 81.191417 iter 100 value 81.006134 final value 81.006134 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.536858 iter 10 value 93.212706 iter 20 value 89.875508 iter 30 value 85.245585 iter 40 value 84.175722 iter 50 value 83.962781 iter 60 value 83.896580 iter 70 value 83.803653 iter 80 value 83.789066 iter 90 value 83.748930 iter 100 value 83.125935 final value 83.125935 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.582664 iter 10 value 94.058303 iter 20 value 92.514759 iter 30 value 92.089914 iter 40 value 91.821287 iter 50 value 91.624835 iter 60 value 90.976361 iter 70 value 86.011768 iter 80 value 82.106877 iter 90 value 81.521918 iter 100 value 81.303466 final value 81.303466 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 105.601133 iter 10 value 93.769877 iter 20 value 87.622814 iter 30 value 86.755194 iter 40 value 84.654062 iter 50 value 83.952922 iter 60 value 83.568436 iter 70 value 83.056524 iter 80 value 82.760586 iter 90 value 82.447159 iter 100 value 81.611830 final value 81.611830 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 119.470924 iter 10 value 94.716274 iter 20 value 94.306055 iter 30 value 87.223851 iter 40 value 85.734043 iter 50 value 83.527743 iter 60 value 82.302905 iter 70 value 81.864163 iter 80 value 81.718799 iter 90 value 81.477828 iter 100 value 81.181515 final value 81.181515 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 120.202709 iter 10 value 94.021443 iter 20 value 91.166311 iter 30 value 87.550345 iter 40 value 87.000773 iter 50 value 82.727187 iter 60 value 81.846875 iter 70 value 81.629045 iter 80 value 81.156393 iter 90 value 80.813192 iter 100 value 80.705627 final value 80.705627 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 113.302508 iter 10 value 94.385560 iter 20 value 93.391870 iter 30 value 87.018225 iter 40 value 86.361104 iter 50 value 84.724161 iter 60 value 82.864192 iter 70 value 82.553741 iter 80 value 82.205551 iter 90 value 81.769369 iter 100 value 81.583278 final value 81.583278 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 113.656592 iter 10 value 94.181475 iter 20 value 90.182189 iter 30 value 85.722930 iter 40 value 83.421901 iter 50 value 82.885183 iter 60 value 82.404227 iter 70 value 81.763927 iter 80 value 81.332646 iter 90 value 81.180347 iter 100 value 80.728483 final value 80.728483 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 107.945221 iter 10 value 93.941022 iter 20 value 89.055282 iter 30 value 88.476151 iter 40 value 86.038514 iter 50 value 84.361250 iter 60 value 83.744158 iter 70 value 83.540673 iter 80 value 83.434944 iter 90 value 83.259378 iter 100 value 82.575193 final value 82.575193 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 117.327682 iter 10 value 93.795891 iter 20 value 93.785387 iter 30 value 93.785168 iter 40 value 93.784770 final value 93.784767 converged Fitting Repeat 2 # weights: 103 initial value 96.103590 final value 93.837756 converged Fitting Repeat 3 # weights: 103 initial value 108.428123 iter 10 value 94.054593 iter 20 value 94.052978 final value 94.052912 converged Fitting Repeat 4 # weights: 103 initial value 102.867357 iter 10 value 93.837595 iter 20 value 93.789007 iter 30 value 93.784256 final value 93.784254 converged Fitting Repeat 5 # weights: 103 initial value 95.416527 iter 10 value 93.837759 final value 93.837737 converged Fitting Repeat 1 # weights: 305 initial value 104.553538 iter 10 value 94.057388 iter 20 value 93.960944 iter 30 value 90.559943 iter 40 value 87.456331 iter 50 value 86.246407 final value 86.246084 converged Fitting Repeat 2 # weights: 305 initial value 94.413599 iter 10 value 94.056004 iter 20 value 93.995805 iter 30 value 87.439925 iter 40 value 85.823116 iter 50 value 85.462340 iter 60 value 85.420598 iter 70 value 85.419897 iter 80 value 85.074983 iter 90 value 84.795946 iter 100 value 84.793985 final value 84.793985 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 96.032524 iter 10 value 93.543754 iter 20 value 93.528362 iter 30 value 93.468685 iter 40 value 93.461107 iter 50 value 91.621561 iter 60 value 90.673172 iter 60 value 90.673172 iter 60 value 90.673172 final value 90.673172 converged Fitting Repeat 4 # weights: 305 initial value 96.148893 iter 10 value 89.499617 iter 20 value 88.805274 iter 30 value 86.944785 iter 40 value 85.431803 iter 50 value 85.229180 iter 60 value 85.228651 iter 60 value 85.228651 final value 85.228642 converged Fitting Repeat 5 # weights: 305 initial value 109.253328 iter 10 value 93.841116 iter 20 value 93.830102 iter 30 value 86.706634 iter 40 value 82.839094 iter 50 value 82.602448 final value 82.600119 converged Fitting Repeat 1 # weights: 507 initial value 104.704978 iter 10 value 90.710717 iter 20 value 88.698860 iter 30 value 88.550811 iter 40 value 88.547322 iter 50 value 88.546274 iter 60 value 86.782352 iter 70 value 82.107401 iter 80 value 80.546885 iter 90 value 80.391172 iter 100 value 80.344504 final value 80.344504 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 111.911249 iter 10 value 93.681719 iter 20 value 93.672974 iter 30 value 93.533775 iter 40 value 93.479599 iter 50 value 93.474684 iter 60 value 92.445288 iter 70 value 91.659937 iter 80 value 91.659198 iter 90 value 90.868516 iter 100 value 86.191727 final value 86.191727 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 115.116698 iter 10 value 93.844066 iter 20 value 93.841841 iter 30 value 93.691023 iter 40 value 91.631055 iter 50 value 91.479766 iter 60 value 91.478208 iter 70 value 91.477146 iter 70 value 91.477146 final value 91.477107 converged Fitting Repeat 4 # weights: 507 initial value 102.176410 iter 10 value 94.061532 iter 20 value 94.038603 final value 93.836771 converged Fitting Repeat 5 # weights: 507 initial value 100.314756 iter 10 value 94.058961 iter 20 value 93.694243 iter 30 value 86.594903 iter 40 value 84.730685 iter 50 value 82.591769 iter 60 value 82.109839 iter 70 value 82.087001 iter 80 value 82.007610 iter 90 value 81.572924 iter 100 value 79.272796 final value 79.272796 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 121.410164 iter 10 value 117.895015 iter 20 value 117.789311 iter 30 value 111.577384 iter 40 value 105.502692 iter 50 value 105.299547 iter 60 value 105.296966 iter 70 value 104.260135 iter 80 value 102.810532 iter 90 value 102.655923 iter 100 value 102.236840 final value 102.236840 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 125.782584 iter 10 value 117.763942 iter 20 value 117.759526 iter 30 value 114.388405 iter 40 value 111.235011 iter 50 value 111.228042 iter 60 value 111.227502 iter 70 value 106.892753 iter 80 value 105.408042 iter 90 value 105.052889 iter 100 value 104.843168 final value 104.843168 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 130.837152 iter 10 value 117.895163 iter 20 value 117.890346 iter 30 value 113.516266 iter 40 value 106.109997 iter 50 value 100.994099 iter 60 value 100.267609 iter 70 value 99.986224 iter 80 value 99.454421 iter 90 value 99.424809 final value 99.424574 converged Fitting Repeat 4 # weights: 305 initial value 120.022145 iter 10 value 117.211124 iter 20 value 115.240965 iter 30 value 115.007390 iter 40 value 114.732198 final value 114.727272 converged Fitting Repeat 5 # weights: 305 initial value 125.546258 iter 10 value 117.895369 iter 20 value 117.890388 final value 117.890329 converged 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 -- Fri May 3 22:39:08 2024 *********************************************** Number of test functions: 7 Number of errors: 0 Number of failures: 0 1 Test Suite : HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures Number of test functions: 7 Number of errors: 0 Number of failures: 0 Warning messages: 1: `repeats` has no meaning for this resampling method. 2: executing %dopar% sequentially: no parallel backend registered > > > > > proc.time() user system elapsed 41.901 2.073 50.387
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 35.116 | 1.989 | 37.567 | |
FreqInteractors | 0.274 | 0.016 | 0.294 | |
calculateAAC | 0.043 | 0.007 | 0.051 | |
calculateAutocor | 0.402 | 0.080 | 0.488 | |
calculateCTDC | 0.087 | 0.005 | 0.093 | |
calculateCTDD | 0.692 | 0.030 | 0.731 | |
calculateCTDT | 0.259 | 0.011 | 0.272 | |
calculateCTriad | 0.431 | 0.028 | 0.465 | |
calculateDC | 0.110 | 0.014 | 0.126 | |
calculateF | 0.389 | 0.014 | 0.408 | |
calculateKSAAP | 0.115 | 0.010 | 0.126 | |
calculateQD_Sm | 1.823 | 0.120 | 1.958 | |
calculateTC | 1.977 | 0.204 | 2.197 | |
calculateTC_Sm | 0.292 | 0.018 | 0.314 | |
corr_plot | 35.131 | 1.915 | 37.405 | |
enrichfindP | 0.511 | 0.067 | 19.623 | |
enrichfind_hp | 0.077 | 0.026 | 2.035 | |
enrichplot | 0.423 | 0.011 | 0.443 | |
filter_missing_values | 0.001 | 0.000 | 0.002 | |
getFASTA | 0.075 | 0.012 | 4.132 | |
getHPI | 0.000 | 0.001 | 0.000 | |
get_negativePPI | 0.002 | 0.001 | 0.002 | |
get_positivePPI | 0.000 | 0.000 | 0.001 | |
impute_missing_data | 0.001 | 0.000 | 0.002 | |
plotPPI | 0.075 | 0.002 | 0.078 | |
pred_ensembel | 14.793 | 0.587 | 11.418 | |
var_imp | 37.207 | 2.177 | 39.941 | |