Back to Multiple platform build/check report for BioC 3.21: simplified long |
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This page was generated on 2025-03-17 11:41 -0400 (Mon, 17 Mar 2025).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
palomino7 | Windows Server 2022 Datacenter | x64 | R Under development (unstable) (2025-03-01 r87860 ucrt) -- "Unsuffered Consequences" | 4545 |
lconway | macOS 12.7.1 Monterey | x86_64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4576 |
kjohnson3 | macOS 13.7.1 Ventura | arm64 | R Under development (unstable) (2025-03-02 r87868) -- "Unsuffered Consequences" | 4528 |
kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4459 |
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 989/2313 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.13.0 (landing page) Matineh Rahmatbakhsh
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | |||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | OK | OK | ![]() | ||||||||
kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
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. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
Package: HPiP |
Version: 1.13.0 |
Command: /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.13.0.tar.gz |
StartedAt: 2025-03-17 07:22:07 -0000 (Mon, 17 Mar 2025) |
EndedAt: 2025-03-17 07:29:04 -0000 (Mon, 17 Mar 2025) |
EllapsedTime: 416.5 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.13.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’ * using R Under development (unstable) (2025-02-19 r87757) * using platform: aarch64-unknown-linux-gnu * R was compiled by aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0 GNU Fortran (GCC) 14.2.0 * running under: openEuler 24.03 (LTS-SP1) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘HPiP/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘HPiP’ version ‘1.13.0’ * 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 loading without being on the library search path ... 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 ... INFO 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 39.318 0.459 39.846 corr_plot 37.730 0.024 37.973 FSmethod 37.316 0.248 37.637 pred_ensembel 18.327 0.513 17.883 enrichfindP 0.530 0.035 19.302 getFASTA 0.127 0.012 5.762 * 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: 2 NOTEs See ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’ for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/R/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.13.0’ ** 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 Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: aarch64-unknown-linux-gnu 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 95.740506 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 103.218674 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 97.862315 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 98.759671 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 96.559913 iter 10 value 93.628462 final value 93.628453 converged Fitting Repeat 1 # weights: 305 initial value 104.654230 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 99.896061 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 101.141417 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 99.307669 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 109.452553 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 120.412628 final value 94.052910 converged Fitting Repeat 2 # weights: 507 initial value 99.216814 final value 93.987879 converged Fitting Repeat 3 # weights: 507 initial value 98.479070 iter 10 value 93.867391 iter 10 value 93.867391 iter 10 value 93.867391 final value 93.867391 converged Fitting Repeat 4 # weights: 507 initial value 94.472664 final value 93.628453 converged Fitting Repeat 5 # weights: 507 initial value 122.058024 iter 10 value 93.543217 final value 93.543210 converged Fitting Repeat 1 # weights: 103 initial value 104.460953 iter 10 value 93.766203 iter 20 value 91.808413 iter 30 value 90.271491 iter 40 value 90.060194 iter 50 value 89.923897 iter 60 value 89.827808 iter 70 value 89.775746 final value 89.774652 converged Fitting Repeat 2 # weights: 103 initial value 97.124430 iter 10 value 94.054325 iter 20 value 93.542339 iter 30 value 89.646228 iter 40 value 84.614074 iter 50 value 83.869964 iter 60 value 82.629738 iter 70 value 80.905929 iter 80 value 80.823688 iter 90 value 80.485255 iter 100 value 80.196950 final value 80.196950 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 104.866594 iter 10 value 92.969452 iter 20 value 84.546941 iter 30 value 84.211386 iter 40 value 84.095354 iter 50 value 84.030079 iter 60 value 83.919973 iter 70 value 82.575705 iter 80 value 81.924645 iter 90 value 81.568088 iter 100 value 81.511105 final value 81.511105 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 99.557677 iter 10 value 94.015174 iter 20 value 93.919489 iter 30 value 93.919122 iter 40 value 93.750536 iter 50 value 87.849610 iter 60 value 85.565479 iter 70 value 84.784163 iter 80 value 83.121979 iter 90 value 82.016620 iter 100 value 81.850085 final value 81.850085 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 99.225262 iter 10 value 94.055922 iter 20 value 88.488216 iter 30 value 84.600303 iter 40 value 83.127697 iter 50 value 82.373275 iter 60 value 82.237430 iter 70 value 82.229886 iter 70 value 82.229886 iter 70 value 82.229886 final value 82.229886 converged Fitting Repeat 1 # weights: 305 initial value 104.508815 iter 10 value 93.859222 iter 20 value 91.664656 iter 30 value 91.044143 iter 40 value 81.744366 iter 50 value 79.538755 iter 60 value 79.095768 iter 70 value 78.986607 iter 80 value 78.570802 iter 90 value 78.385506 iter 100 value 78.176996 final value 78.176996 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 106.627415 iter 10 value 93.471081 iter 20 value 90.808320 iter 30 value 89.974404 iter 40 value 89.863093 iter 50 value 89.761012 iter 60 value 88.838041 iter 70 value 83.233989 iter 80 value 81.560977 iter 90 value 80.150258 iter 100 value 79.743830 final value 79.743830 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 102.288487 iter 10 value 93.146407 iter 20 value 85.206019 iter 30 value 84.396724 iter 40 value 80.802511 iter 50 value 79.843939 iter 60 value 79.232059 iter 70 value 78.891979 iter 80 value 78.641878 iter 90 value 78.584081 iter 100 value 78.567031 final value 78.567031 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.008188 iter 10 value 94.251327 iter 20 value 91.932199 iter 30 value 84.380629 iter 40 value 84.091529 iter 50 value 83.418529 iter 60 value 82.808489 iter 70 value 82.764858 iter 80 value 82.078129 iter 90 value 80.761139 iter 100 value 80.453729 final value 80.453729 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 99.528241 iter 10 value 94.347643 iter 20 value 94.041264 iter 30 value 93.826611 iter 40 value 93.561224 iter 50 value 89.807234 iter 60 value 89.460599 iter 70 value 85.856130 iter 80 value 82.916551 iter 90 value 79.868530 iter 100 value 79.365793 final value 79.365793 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 110.120708 iter 10 value 95.056680 iter 20 value 88.586060 iter 30 value 83.529638 iter 40 value 81.344355 iter 50 value 79.559651 iter 60 value 79.283180 iter 70 value 78.910465 iter 80 value 78.725656 iter 90 value 78.689460 iter 100 value 78.543232 final value 78.543232 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 122.182737 iter 10 value 93.942042 iter 20 value 86.252799 iter 30 value 85.159530 iter 40 value 83.635696 iter 50 value 81.423683 iter 60 value 78.698752 iter 70 value 78.213097 iter 80 value 78.081883 iter 90 value 77.960208 iter 100 value 77.847129 final value 77.847129 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 107.231418 iter 10 value 94.422443 iter 20 value 93.499574 iter 30 value 91.677195 iter 40 value 90.824251 iter 50 value 90.592496 iter 60 value 88.468171 iter 70 value 84.900138 iter 80 value 82.546082 iter 90 value 81.164831 iter 100 value 80.369489 final value 80.369489 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 102.389755 iter 10 value 91.661833 iter 20 value 87.521641 iter 30 value 86.131686 iter 40 value 85.794387 iter 50 value 85.309324 iter 60 value 80.958978 iter 70 value 80.409975 iter 80 value 80.034245 iter 90 value 79.335605 iter 100 value 78.896296 final value 78.896296 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 136.146393 iter 10 value 94.182976 iter 20 value 89.241225 iter 30 value 86.230313 iter 40 value 84.100823 iter 50 value 81.229454 iter 60 value 79.524863 iter 70 value 79.353492 iter 80 value 79.030745 iter 90 value 78.591362 iter 100 value 78.428161 final value 78.428161 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 94.341279 final value 94.054660 converged Fitting Repeat 2 # weights: 103 initial value 95.117085 iter 10 value 93.630072 iter 20 value 93.458306 iter 30 value 83.013989 iter 40 value 81.634685 final value 81.556859 converged Fitting Repeat 3 # weights: 103 initial value 97.705521 final value 94.054555 converged Fitting Repeat 4 # weights: 103 initial value 98.911810 iter 10 value 94.054658 iter 20 value 94.052976 iter 30 value 93.526474 final value 92.540210 converged Fitting Repeat 5 # weights: 103 initial value 102.231734 final value 93.899066 converged Fitting Repeat 1 # weights: 305 initial value 103.811588 iter 10 value 93.524552 iter 20 value 93.521115 iter 30 value 87.125981 iter 40 value 86.161099 final value 86.146353 converged Fitting Repeat 2 # weights: 305 initial value 103.585900 iter 10 value 94.058210 iter 20 value 93.998764 iter 30 value 93.097406 iter 40 value 93.096764 iter 50 value 93.035941 iter 60 value 93.031365 final value 93.031364 converged Fitting Repeat 3 # weights: 305 initial value 95.973566 iter 10 value 93.427545 iter 20 value 91.770006 iter 30 value 91.766638 iter 40 value 87.511805 iter 50 value 82.905838 iter 60 value 82.851941 iter 70 value 82.371875 iter 80 value 81.189325 iter 90 value 81.181750 iter 100 value 81.170692 final value 81.170692 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 105.627507 iter 10 value 94.057389 iter 20 value 93.833192 iter 30 value 89.565534 iter 40 value 88.589368 iter 50 value 82.243743 iter 60 value 82.238118 iter 70 value 82.185664 iter 80 value 81.001181 iter 90 value 78.366725 iter 100 value 78.243948 final value 78.243948 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 98.028840 iter 10 value 93.872180 iter 20 value 93.832586 iter 30 value 93.055177 iter 40 value 91.599244 iter 50 value 91.272101 iter 60 value 91.251542 iter 70 value 91.251336 iter 70 value 91.251336 iter 70 value 91.251336 final value 91.251336 converged Fitting Repeat 1 # weights: 507 initial value 110.689572 iter 10 value 93.231314 iter 20 value 93.226994 iter 30 value 93.182278 iter 40 value 88.162857 iter 50 value 87.728252 iter 60 value 87.695981 iter 70 value 87.695554 iter 80 value 87.390208 iter 90 value 81.804393 iter 100 value 80.249777 final value 80.249777 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 115.102280 iter 10 value 89.026306 iter 20 value 86.062676 iter 30 value 86.046549 iter 40 value 86.044908 iter 50 value 86.040290 iter 60 value 83.595033 iter 70 value 83.125568 iter 80 value 80.522164 iter 90 value 78.889701 iter 100 value 77.949665 final value 77.949665 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 106.392999 iter 10 value 93.744689 iter 20 value 93.034600 iter 30 value 92.812497 iter 40 value 92.811955 iter 50 value 92.535564 iter 60 value 88.362776 iter 70 value 86.030108 iter 80 value 86.029167 iter 90 value 84.179782 iter 100 value 82.665407 final value 82.665407 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 131.309018 iter 10 value 93.832748 iter 20 value 93.825133 iter 30 value 93.739295 iter 40 value 91.934981 iter 50 value 90.112921 iter 60 value 84.565487 iter 70 value 83.397365 iter 80 value 83.392544 iter 90 value 83.391568 iter 100 value 83.384184 final value 83.384184 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 113.933709 iter 10 value 93.875888 iter 20 value 93.872158 iter 30 value 93.870368 iter 40 value 93.859702 iter 50 value 90.136778 iter 60 value 87.031812 iter 70 value 86.810065 iter 80 value 86.802464 final value 86.802196 converged Fitting Repeat 1 # weights: 103 initial value 96.652921 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 95.887325 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 103.077389 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 96.356539 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 97.142108 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 104.310502 final value 93.991525 converged Fitting Repeat 2 # weights: 305 initial value 97.823946 iter 10 value 93.499474 iter 20 value 91.988556 iter 30 value 91.987135 final value 91.987133 converged Fitting Repeat 3 # weights: 305 initial value 101.744837 iter 10 value 93.582419 iter 10 value 93.582418 iter 10 value 93.582418 final value 93.582418 converged Fitting Repeat 4 # weights: 305 initial value 104.986306 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 98.253219 iter 10 value 93.582418 iter 10 value 93.582418 iter 10 value 93.582418 final value 93.582418 converged Fitting Repeat 1 # weights: 507 initial value 102.948448 iter 10 value 93.461620 final value 93.458062 converged Fitting Repeat 2 # weights: 507 initial value 94.510665 iter 10 value 85.988719 iter 20 value 85.024600 iter 30 value 85.010064 final value 85.010019 converged Fitting Repeat 3 # weights: 507 initial value 93.836728 final value 93.582418 converged Fitting Repeat 4 # weights: 507 initial value 114.436448 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 99.873403 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 95.754501 iter 10 value 93.576207 iter 20 value 88.829148 iter 30 value 86.671124 iter 40 value 86.336197 iter 50 value 85.974259 iter 60 value 85.455213 iter 70 value 85.207743 iter 80 value 85.181785 final value 85.181770 converged Fitting Repeat 2 # weights: 103 initial value 103.328667 iter 10 value 94.012333 iter 20 value 93.636751 iter 30 value 93.603065 iter 40 value 87.839506 iter 50 value 86.916540 iter 60 value 85.339745 iter 70 value 84.087020 iter 80 value 83.701855 iter 90 value 83.159558 iter 100 value 83.141217 final value 83.141217 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 97.405738 iter 10 value 94.055342 iter 20 value 93.840768 iter 30 value 86.955881 iter 40 value 86.460019 iter 50 value 85.926009 iter 60 value 85.283468 iter 70 value 84.885229 iter 80 value 83.625699 iter 90 value 83.164768 iter 100 value 83.108545 final value 83.108545 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 106.195330 iter 10 value 94.031396 iter 20 value 93.509265 iter 30 value 87.581768 iter 40 value 86.321896 iter 50 value 85.697136 iter 60 value 85.116885 iter 70 value 84.940026 iter 80 value 84.831970 iter 90 value 84.817781 final value 84.817771 converged Fitting Repeat 5 # weights: 103 initial value 106.539562 iter 10 value 94.057470 iter 20 value 92.733052 iter 30 value 91.954610 iter 40 value 87.489749 iter 50 value 86.580623 iter 60 value 86.307571 iter 70 value 85.827410 iter 80 value 85.417601 final value 85.417568 converged Fitting Repeat 1 # weights: 305 initial value 114.789482 iter 10 value 93.911714 iter 20 value 89.463147 iter 30 value 85.735685 iter 40 value 85.141333 iter 50 value 84.664523 iter 60 value 84.011314 iter 70 value 83.334628 iter 80 value 83.125299 iter 90 value 83.035599 iter 100 value 82.670063 final value 82.670063 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 99.479254 iter 10 value 94.095441 iter 20 value 94.008476 iter 30 value 93.000777 iter 40 value 89.904140 iter 50 value 87.700982 iter 60 value 84.602831 iter 70 value 82.976196 iter 80 value 82.202630 iter 90 value 81.969765 iter 100 value 81.649867 final value 81.649867 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.923300 iter 10 value 94.015298 iter 20 value 93.637940 iter 30 value 93.561184 iter 40 value 91.884335 iter 50 value 88.149981 iter 60 value 86.714240 iter 70 value 85.056715 iter 80 value 83.358950 iter 90 value 83.150875 iter 100 value 82.325211 final value 82.325211 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.510777 iter 10 value 94.209933 iter 20 value 94.025916 iter 30 value 93.634140 iter 40 value 87.774101 iter 50 value 86.652815 iter 60 value 85.671952 iter 70 value 82.764627 iter 80 value 81.899872 iter 90 value 81.687804 iter 100 value 81.599302 final value 81.599302 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 111.124626 iter 10 value 93.893343 iter 20 value 91.152326 iter 30 value 87.935199 iter 40 value 85.699752 iter 50 value 85.559998 iter 60 value 85.159414 iter 70 value 82.825369 iter 80 value 82.051882 iter 90 value 81.445616 iter 100 value 81.279536 final value 81.279536 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 103.843209 iter 10 value 93.617932 iter 20 value 92.633298 iter 30 value 86.271698 iter 40 value 85.992132 iter 50 value 84.987810 iter 60 value 83.703887 iter 70 value 83.526287 iter 80 value 83.503466 iter 90 value 83.308916 iter 100 value 82.774147 final value 82.774147 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 108.435460 iter 10 value 95.355947 iter 20 value 86.671826 iter 30 value 84.952370 iter 40 value 83.604147 iter 50 value 83.126458 iter 60 value 83.002879 iter 70 value 82.987124 iter 80 value 82.960998 iter 90 value 82.762458 iter 100 value 82.516909 final value 82.516909 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 132.850467 iter 10 value 94.523629 iter 20 value 91.406451 iter 30 value 87.113943 iter 40 value 86.502388 iter 50 value 85.965739 iter 60 value 85.705318 iter 70 value 85.602552 iter 80 value 84.578203 iter 90 value 83.242932 iter 100 value 82.084131 final value 82.084131 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 123.010144 iter 10 value 94.548958 iter 20 value 88.361747 iter 30 value 86.044661 iter 40 value 85.470077 iter 50 value 84.454573 iter 60 value 82.710433 iter 70 value 81.984551 iter 80 value 81.933695 iter 90 value 81.928889 iter 100 value 81.898834 final value 81.898834 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 106.609124 iter 10 value 94.176354 iter 20 value 90.538825 iter 30 value 88.395658 iter 40 value 85.920948 iter 50 value 83.405749 iter 60 value 82.029151 iter 70 value 81.735082 iter 80 value 81.282125 iter 90 value 81.231782 iter 100 value 81.175091 final value 81.175091 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.385877 final value 94.054400 converged Fitting Repeat 2 # weights: 103 initial value 102.076024 final value 94.054758 converged Fitting Repeat 3 # weights: 103 initial value 99.630066 final value 94.054362 converged Fitting Repeat 4 # weights: 103 initial value 109.029973 final value 94.054357 converged Fitting Repeat 5 # weights: 103 initial value 94.385495 final value 94.054356 converged Fitting Repeat 1 # weights: 305 initial value 112.976134 iter 10 value 94.057773 final value 94.052952 converged Fitting Repeat 2 # weights: 305 initial value 105.704484 iter 10 value 94.013486 iter 20 value 94.009205 iter 30 value 90.893273 iter 40 value 84.621731 iter 50 value 84.274730 iter 60 value 84.167135 iter 70 value 84.061612 iter 80 value 83.538570 iter 90 value 83.294718 final value 83.176395 converged Fitting Repeat 3 # weights: 305 initial value 100.650363 iter 10 value 94.058286 iter 20 value 94.000924 iter 30 value 93.593792 final value 93.593779 converged Fitting Repeat 4 # weights: 305 initial value 98.502313 iter 10 value 94.057639 iter 20 value 94.055448 iter 30 value 94.048446 iter 40 value 91.543595 iter 50 value 86.741954 iter 60 value 86.663620 final value 86.646767 converged Fitting Repeat 5 # weights: 305 initial value 106.021211 iter 10 value 90.075330 iter 20 value 88.002772 iter 30 value 87.907033 iter 40 value 87.882420 iter 50 value 86.622468 iter 60 value 86.619226 iter 70 value 86.618539 iter 80 value 85.686238 iter 90 value 85.313120 iter 100 value 85.312813 final value 85.312813 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 97.795368 iter 10 value 86.046281 iter 20 value 83.710777 iter 30 value 83.681892 iter 40 value 83.645252 iter 50 value 83.580824 iter 60 value 83.531477 iter 70 value 83.529673 iter 80 value 83.528827 iter 90 value 83.528409 iter 100 value 83.527557 final value 83.527557 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 100.344978 iter 10 value 93.960579 iter 20 value 92.448682 iter 30 value 92.427914 iter 40 value 92.404844 iter 50 value 92.178711 iter 60 value 92.167347 iter 70 value 91.991530 iter 80 value 91.975519 iter 90 value 91.973188 iter 100 value 91.807788 final value 91.807788 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 109.008267 iter 10 value 93.590690 iter 20 value 93.477785 iter 30 value 93.447960 iter 40 value 93.444650 iter 50 value 93.444298 iter 60 value 93.442317 iter 70 value 93.434256 iter 80 value 83.579226 iter 90 value 81.495638 iter 100 value 80.639854 final value 80.639854 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 97.395938 iter 10 value 93.579530 iter 20 value 93.510466 iter 30 value 92.392891 iter 40 value 88.503582 iter 50 value 84.244517 iter 60 value 83.509992 iter 70 value 82.230643 iter 80 value 82.211169 iter 90 value 82.156555 iter 100 value 81.827914 final value 81.827914 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 110.495806 iter 10 value 94.060724 iter 20 value 94.052987 iter 30 value 93.619996 final value 93.582831 converged Fitting Repeat 1 # weights: 103 initial value 102.939066 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 109.821805 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 101.324208 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 94.603520 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 100.349915 final value 94.443243 converged Fitting Repeat 1 # weights: 305 initial value 98.270602 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 96.807398 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 127.836314 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 100.264674 final value 94.275362 converged Fitting Repeat 5 # weights: 305 initial value 95.164986 final value 94.275362 converged Fitting Repeat 1 # weights: 507 initial value 105.086571 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 120.099731 iter 10 value 93.838662 iter 20 value 87.559837 iter 30 value 86.947232 iter 40 value 85.433378 iter 50 value 84.956809 iter 60 value 84.956541 iter 60 value 84.956541 iter 60 value 84.956541 final value 84.956541 converged Fitting Repeat 3 # weights: 507 initial value 97.710698 final value 94.203915 converged Fitting Repeat 4 # weights: 507 initial value 100.499278 iter 10 value 86.003098 iter 20 value 85.952221 iter 30 value 85.948748 final value 85.948718 converged Fitting Repeat 5 # weights: 507 initial value 103.492129 iter 10 value 86.722643 iter 20 value 85.999121 iter 30 value 85.965710 final value 85.965640 converged Fitting Repeat 1 # weights: 103 initial value 99.768278 iter 10 value 93.815251 iter 20 value 92.244077 iter 30 value 90.615913 iter 40 value 86.207492 iter 50 value 85.903667 iter 60 value 85.478386 iter 70 value 84.653645 iter 80 value 84.256934 iter 90 value 84.171681 final value 84.163219 converged Fitting Repeat 2 # weights: 103 initial value 99.399761 iter 10 value 94.253813 iter 20 value 86.367331 iter 30 value 86.048306 iter 40 value 85.837921 iter 50 value 84.719130 iter 60 value 84.306750 iter 70 value 84.164186 final value 84.163218 converged Fitting Repeat 3 # weights: 103 initial value 106.330407 iter 10 value 94.101410 iter 20 value 90.047001 iter 30 value 88.047487 iter 40 value 85.908647 iter 50 value 84.265765 iter 60 value 82.603657 iter 70 value 81.938444 iter 80 value 81.760406 iter 90 value 81.597667 iter 100 value 81.589370 final value 81.589370 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 99.592613 iter 10 value 91.589204 iter 20 value 84.535064 iter 30 value 84.376616 iter 40 value 84.169281 iter 50 value 83.998611 iter 60 value 82.895273 iter 70 value 82.465176 iter 80 value 81.964375 iter 90 value 81.930903 iter 100 value 81.905040 final value 81.905040 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 106.409260 iter 10 value 94.489077 iter 20 value 91.185064 iter 30 value 87.050562 iter 40 value 84.679694 iter 50 value 84.436983 iter 60 value 84.411905 final value 84.411878 converged Fitting Repeat 1 # weights: 305 initial value 103.248733 iter 10 value 95.072213 iter 20 value 94.199862 iter 30 value 94.190180 iter 40 value 87.558370 iter 50 value 84.767099 iter 60 value 83.675438 iter 70 value 82.246457 iter 80 value 81.693546 iter 90 value 81.532855 iter 100 value 81.003490 final value 81.003490 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 100.647597 iter 10 value 94.169792 iter 20 value 89.289979 iter 30 value 84.909050 iter 40 value 83.743462 iter 50 value 82.523734 iter 60 value 82.319980 iter 70 value 81.884826 iter 80 value 81.085052 iter 90 value 80.682524 iter 100 value 80.624229 final value 80.624229 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 124.596644 iter 10 value 94.516531 iter 20 value 93.139358 iter 30 value 88.629365 iter 40 value 88.224360 iter 50 value 86.577441 iter 60 value 85.489402 iter 70 value 84.475041 iter 80 value 84.063187 iter 90 value 82.112779 iter 100 value 81.453552 final value 81.453552 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 116.538216 iter 10 value 94.259657 iter 20 value 86.824588 iter 30 value 86.201129 iter 40 value 85.322240 iter 50 value 84.339398 iter 60 value 84.103912 iter 70 value 83.398437 iter 80 value 82.233661 iter 90 value 81.208137 iter 100 value 80.872333 final value 80.872333 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 119.699680 iter 10 value 94.478850 iter 20 value 92.446405 iter 30 value 85.904433 iter 40 value 84.627100 iter 50 value 82.715994 iter 60 value 81.337872 iter 70 value 80.929642 iter 80 value 80.770807 iter 90 value 80.376019 iter 100 value 80.214282 final value 80.214282 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 110.011376 iter 10 value 95.226255 iter 20 value 93.948651 iter 30 value 88.541473 iter 40 value 85.291352 iter 50 value 83.781607 iter 60 value 83.184535 iter 70 value 81.776231 iter 80 value 80.997743 iter 90 value 80.652948 iter 100 value 80.480792 final value 80.480792 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 112.506450 iter 10 value 94.409066 iter 20 value 89.591310 iter 30 value 86.269459 iter 40 value 85.874547 iter 50 value 84.491801 iter 60 value 83.965536 iter 70 value 83.566939 iter 80 value 82.839769 iter 90 value 81.745592 iter 100 value 81.308922 final value 81.308922 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 111.895036 iter 10 value 94.887920 iter 20 value 85.417083 iter 30 value 84.293221 iter 40 value 82.699009 iter 50 value 81.600379 iter 60 value 80.742758 iter 70 value 80.603304 iter 80 value 80.291008 iter 90 value 80.093146 iter 100 value 79.994594 final value 79.994594 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 115.915778 iter 10 value 94.882690 iter 20 value 89.016079 iter 30 value 88.643042 iter 40 value 85.827899 iter 50 value 84.068764 iter 60 value 83.325666 iter 70 value 82.373547 iter 80 value 80.936220 iter 90 value 80.159437 iter 100 value 79.917472 final value 79.917472 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 117.571137 iter 10 value 94.508668 iter 20 value 92.797091 iter 30 value 86.466089 iter 40 value 84.951662 iter 50 value 84.034092 iter 60 value 82.448046 iter 70 value 80.882161 iter 80 value 79.973172 iter 90 value 79.769432 iter 100 value 79.645386 final value 79.645386 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.283567 final value 94.486065 converged Fitting Repeat 2 # weights: 103 initial value 100.586894 final value 94.485849 converged Fitting Repeat 3 # weights: 103 initial value 105.509220 final value 94.485948 converged Fitting Repeat 4 # weights: 103 initial value 107.743672 final value 94.485712 converged Fitting Repeat 5 # weights: 103 initial value 98.261110 final value 94.485814 converged Fitting Repeat 1 # weights: 305 initial value 97.421846 iter 10 value 86.959602 iter 20 value 86.888701 iter 30 value 86.888407 iter 40 value 86.880732 iter 50 value 85.981799 iter 60 value 85.966763 final value 85.966460 converged Fitting Repeat 2 # weights: 305 initial value 98.383480 iter 10 value 94.489253 iter 20 value 94.475072 iter 30 value 93.784532 final value 93.784502 converged Fitting Repeat 3 # weights: 305 initial value 95.616837 iter 10 value 94.279859 iter 20 value 90.720210 iter 30 value 85.247866 iter 40 value 85.240467 iter 50 value 85.107082 iter 60 value 85.025952 iter 70 value 85.024749 final value 85.024085 converged Fitting Repeat 4 # weights: 305 initial value 96.898577 iter 10 value 94.489141 final value 94.484603 converged Fitting Repeat 5 # weights: 305 initial value 125.882484 iter 10 value 94.489007 iter 20 value 94.353430 iter 30 value 90.952840 iter 40 value 86.876510 iter 50 value 86.869558 iter 60 value 86.868910 iter 70 value 85.423498 iter 80 value 85.381685 final value 85.380224 converged Fitting Repeat 1 # weights: 507 initial value 114.918755 iter 10 value 94.273446 iter 20 value 94.258543 iter 30 value 94.034934 iter 40 value 87.150710 iter 50 value 83.376767 iter 60 value 82.365471 iter 70 value 82.284864 final value 82.284853 converged Fitting Repeat 2 # weights: 507 initial value 106.962805 iter 10 value 94.283552 iter 20 value 94.260688 iter 30 value 93.110205 iter 40 value 84.559651 iter 50 value 84.461558 iter 60 value 84.459011 iter 70 value 84.172276 iter 80 value 84.115897 iter 90 value 84.115801 final value 84.115703 converged Fitting Repeat 3 # weights: 507 initial value 110.449191 iter 10 value 94.492118 iter 20 value 94.415113 iter 30 value 92.292125 iter 40 value 89.241515 iter 50 value 86.662527 iter 60 value 85.783632 iter 70 value 85.779609 iter 80 value 85.778632 iter 90 value 84.069716 iter 100 value 83.655981 final value 83.655981 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 100.929371 iter 10 value 94.492209 iter 20 value 94.350358 iter 30 value 92.421783 iter 40 value 92.421157 final value 92.421154 converged Fitting Repeat 5 # weights: 507 initial value 99.563951 iter 10 value 94.166677 iter 20 value 94.161564 iter 30 value 92.918701 iter 40 value 86.100136 iter 50 value 86.086288 iter 60 value 86.070513 iter 70 value 86.063476 iter 80 value 86.063033 iter 90 value 85.892961 iter 100 value 85.770644 final value 85.770644 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.114414 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 103.747202 iter 10 value 92.826627 iter 20 value 82.311707 iter 30 value 82.169130 final value 82.168831 converged Fitting Repeat 3 # weights: 103 initial value 97.468475 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 100.026371 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 95.669253 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 95.740887 iter 10 value 94.396689 iter 20 value 94.395064 final value 94.395062 converged Fitting Repeat 2 # weights: 305 initial value 103.684616 final value 94.026542 converged Fitting Repeat 3 # weights: 305 initial value 99.190937 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 104.333418 final value 93.930685 converged Fitting Repeat 5 # weights: 305 initial value 104.884312 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 98.988740 iter 10 value 92.214675 iter 20 value 84.299640 iter 30 value 84.289259 final value 84.289242 converged Fitting Repeat 2 # weights: 507 initial value 97.578931 final value 94.026542 converged Fitting Repeat 3 # weights: 507 initial value 104.916169 final value 94.057229 converged Fitting Repeat 4 # weights: 507 initial value 107.269260 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 109.444039 final value 94.026542 converged Fitting Repeat 1 # weights: 103 initial value 102.233973 iter 10 value 90.380175 iter 20 value 82.968429 iter 30 value 82.867961 iter 40 value 82.751899 iter 50 value 82.703328 final value 82.702611 converged Fitting Repeat 2 # weights: 103 initial value 100.297411 iter 10 value 95.962325 iter 20 value 92.156961 iter 30 value 83.722308 iter 40 value 83.088229 iter 50 value 83.041246 final value 83.041115 converged Fitting Repeat 3 # weights: 103 initial value 98.299616 iter 10 value 94.092427 iter 20 value 89.796707 iter 30 value 83.336939 iter 40 value 83.158278 iter 50 value 83.147922 iter 60 value 82.944468 iter 70 value 82.769663 iter 80 value 82.741607 iter 90 value 82.695587 final value 82.693106 converged Fitting Repeat 4 # weights: 103 initial value 118.314138 iter 10 value 94.232384 iter 20 value 86.308344 iter 30 value 85.429635 iter 40 value 83.302556 iter 50 value 83.057716 iter 60 value 83.041303 final value 83.041300 converged Fitting Repeat 5 # weights: 103 initial value 102.787844 iter 10 value 94.183316 iter 20 value 93.023328 iter 30 value 85.595541 iter 40 value 83.242885 iter 50 value 82.827396 iter 60 value 82.703036 final value 82.702612 converged Fitting Repeat 1 # weights: 305 initial value 111.216463 iter 10 value 94.455550 iter 20 value 89.752124 iter 30 value 86.227102 iter 40 value 84.821333 iter 50 value 80.780091 iter 60 value 80.108645 iter 70 value 79.831828 iter 80 value 79.676996 iter 90 value 79.622497 iter 100 value 79.412059 final value 79.412059 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 103.192694 iter 10 value 94.588529 iter 20 value 93.865802 iter 30 value 85.280665 iter 40 value 83.103137 iter 50 value 82.822980 iter 60 value 81.039113 iter 70 value 80.866240 iter 80 value 80.800153 iter 90 value 80.653579 iter 100 value 80.492984 final value 80.492984 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 99.893101 iter 10 value 94.851627 iter 20 value 87.660045 iter 30 value 84.771089 iter 40 value 84.694440 iter 50 value 83.185687 iter 60 value 82.723754 iter 70 value 82.126190 iter 80 value 80.403207 iter 90 value 79.685721 iter 100 value 79.436319 final value 79.436319 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 113.941169 iter 10 value 94.442565 iter 20 value 93.776107 iter 30 value 90.068260 iter 40 value 83.729249 iter 50 value 83.039828 iter 60 value 82.721613 iter 70 value 82.377415 iter 80 value 82.288929 iter 90 value 81.432321 iter 100 value 80.326766 final value 80.326766 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.579526 iter 10 value 94.595691 iter 20 value 89.228161 iter 30 value 84.130610 iter 40 value 83.060304 iter 50 value 82.292586 iter 60 value 80.821429 iter 70 value 80.358066 iter 80 value 79.759729 iter 90 value 79.419800 iter 100 value 79.305067 final value 79.305067 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 113.528667 iter 10 value 95.149311 iter 20 value 94.270453 iter 30 value 85.452214 iter 40 value 84.543905 iter 50 value 81.848350 iter 60 value 80.473972 iter 70 value 80.049237 iter 80 value 79.617475 iter 90 value 79.411171 iter 100 value 79.077848 final value 79.077848 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 107.195616 iter 10 value 94.403356 iter 20 value 85.407890 iter 30 value 84.845283 iter 40 value 82.751762 iter 50 value 82.417126 iter 60 value 82.296201 iter 70 value 82.040774 iter 80 value 79.997961 iter 90 value 79.047606 iter 100 value 78.911091 final value 78.911091 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 108.034487 iter 10 value 94.320564 iter 20 value 90.994247 iter 30 value 86.847569 iter 40 value 83.914638 iter 50 value 81.880349 iter 60 value 81.408489 iter 70 value 81.223998 iter 80 value 80.983910 iter 90 value 80.451292 iter 100 value 79.760714 final value 79.760714 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 110.563228 iter 10 value 94.438958 iter 20 value 88.611312 iter 30 value 86.905992 iter 40 value 86.607116 iter 50 value 84.418468 iter 60 value 81.330561 iter 70 value 79.677103 iter 80 value 79.277632 iter 90 value 79.123538 iter 100 value 78.901491 final value 78.901491 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 115.592941 iter 10 value 94.844120 iter 20 value 88.542195 iter 30 value 84.982052 iter 40 value 83.891993 iter 50 value 82.334563 iter 60 value 81.371273 iter 70 value 80.382061 iter 80 value 80.021519 iter 90 value 79.627009 iter 100 value 79.587184 final value 79.587184 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 103.923053 final value 94.485797 converged Fitting Repeat 2 # weights: 103 initial value 107.593701 iter 10 value 94.487106 iter 20 value 94.484262 final value 94.484225 converged Fitting Repeat 3 # weights: 103 initial value 96.254452 iter 10 value 84.735216 iter 20 value 84.304809 iter 30 value 84.300448 iter 40 value 84.012640 iter 50 value 84.008393 iter 60 value 84.004990 final value 84.004977 converged Fitting Repeat 4 # weights: 103 initial value 98.162085 iter 10 value 94.485899 iter 20 value 94.419117 iter 30 value 84.297642 iter 40 value 84.292867 iter 50 value 84.291639 iter 60 value 84.006003 final value 84.006002 converged Fitting Repeat 5 # weights: 103 initial value 96.494218 final value 94.486036 converged Fitting Repeat 1 # weights: 305 initial value 96.341066 iter 10 value 94.489185 iter 20 value 94.468750 iter 30 value 94.058397 iter 40 value 93.676198 iter 50 value 84.093029 iter 60 value 84.084308 iter 70 value 84.083737 iter 80 value 83.670467 iter 90 value 82.111739 iter 100 value 81.268002 final value 81.268002 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 98.141339 iter 10 value 93.980626 iter 20 value 93.747311 iter 30 value 93.670059 iter 40 value 93.669484 iter 50 value 83.821955 iter 60 value 82.779202 iter 70 value 81.556660 iter 80 value 81.159179 final value 81.156390 converged Fitting Repeat 3 # weights: 305 initial value 97.069159 iter 10 value 94.488818 iter 20 value 94.227801 iter 30 value 85.690687 iter 40 value 82.831572 iter 50 value 81.941258 iter 60 value 80.956148 iter 70 value 80.926977 iter 80 value 80.637469 iter 90 value 79.501417 iter 100 value 79.346367 final value 79.346367 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 99.632906 iter 10 value 94.488075 iter 20 value 94.247892 iter 30 value 84.945053 iter 40 value 84.728244 iter 50 value 82.315161 iter 60 value 82.254224 final value 82.246623 converged Fitting Repeat 5 # weights: 305 initial value 106.765041 iter 10 value 94.448059 iter 20 value 89.008318 final value 82.314334 converged Fitting Repeat 1 # weights: 507 initial value 98.306896 iter 10 value 94.504274 iter 20 value 94.479943 iter 30 value 93.765042 iter 40 value 93.754075 iter 50 value 93.461483 iter 60 value 86.259635 iter 70 value 81.840633 iter 80 value 81.512340 iter 90 value 81.443400 iter 100 value 80.650599 final value 80.650599 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 101.648624 iter 10 value 93.213266 iter 20 value 84.652688 iter 30 value 83.891045 iter 40 value 81.994906 iter 50 value 81.924521 iter 60 value 81.785358 iter 70 value 81.779125 iter 80 value 81.774733 iter 90 value 81.603811 iter 100 value 80.546987 final value 80.546987 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 102.889130 iter 10 value 94.034803 iter 20 value 94.002717 iter 30 value 84.274107 iter 40 value 83.916965 iter 50 value 83.850154 final value 83.849730 converged Fitting Repeat 4 # weights: 507 initial value 103.087010 iter 10 value 94.491804 iter 20 value 92.122361 iter 30 value 82.159142 iter 40 value 81.774334 iter 40 value 81.774334 iter 40 value 81.774334 final value 81.774334 converged Fitting Repeat 5 # weights: 507 initial value 98.341227 iter 10 value 94.035668 iter 20 value 94.028083 final value 94.027848 converged Fitting Repeat 1 # weights: 103 initial value 97.089305 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 97.053323 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 103.085125 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 98.261816 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 99.402292 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 100.291490 final value 93.637380 converged Fitting Repeat 2 # weights: 305 initial value 99.645487 final value 94.444193 converged Fitting Repeat 3 # weights: 305 initial value 107.667654 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 96.994761 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 103.605741 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 115.785872 iter 10 value 94.466844 final value 94.466822 converged Fitting Repeat 2 # weights: 507 initial value 100.017068 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 101.617505 final value 94.323809 converged Fitting Repeat 4 # weights: 507 initial value 109.789837 final value 94.427726 converged Fitting Repeat 5 # weights: 507 initial value 101.514841 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 101.643911 iter 10 value 94.519442 iter 20 value 94.462670 iter 30 value 89.239437 iter 40 value 86.855121 iter 50 value 85.648804 iter 60 value 85.218880 iter 70 value 85.016218 iter 80 value 84.826442 iter 90 value 82.683947 iter 100 value 82.194405 final value 82.194405 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 97.876566 iter 10 value 94.417334 iter 20 value 93.619249 iter 30 value 93.196609 iter 40 value 86.065310 iter 50 value 85.617943 iter 60 value 84.815952 iter 70 value 84.612392 iter 80 value 84.359654 iter 90 value 83.407100 iter 100 value 82.375929 final value 82.375929 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 100.692101 iter 10 value 94.455126 iter 20 value 92.157808 iter 30 value 90.939973 iter 40 value 85.719700 iter 50 value 84.020270 iter 60 value 83.099548 iter 70 value 82.618491 iter 80 value 82.298157 iter 90 value 82.171264 final value 82.171247 converged Fitting Repeat 4 # weights: 103 initial value 100.895055 iter 10 value 94.528131 iter 20 value 94.489476 iter 30 value 94.404226 iter 40 value 93.927083 iter 50 value 93.388297 iter 60 value 93.313188 iter 70 value 90.347534 iter 80 value 86.569106 iter 90 value 85.422387 iter 100 value 85.020131 final value 85.020131 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 100.178153 iter 10 value 94.464206 iter 20 value 93.456277 iter 30 value 91.425267 iter 40 value 91.350443 iter 50 value 91.344945 iter 60 value 91.344826 iter 70 value 91.324632 iter 80 value 86.559595 iter 90 value 84.857293 iter 100 value 84.553907 final value 84.553907 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 112.775913 iter 10 value 94.712765 iter 20 value 94.286945 iter 30 value 91.740648 iter 40 value 90.082253 iter 50 value 89.627785 iter 60 value 89.246361 iter 70 value 86.723558 iter 80 value 85.608173 iter 90 value 82.971396 iter 100 value 81.981255 final value 81.981255 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 112.049786 iter 10 value 96.212113 iter 20 value 94.497765 iter 30 value 89.735025 iter 40 value 86.635297 iter 50 value 83.897995 iter 60 value 81.966947 iter 70 value 81.691496 iter 80 value 81.662858 iter 90 value 81.334503 iter 100 value 81.177432 final value 81.177432 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 107.157074 iter 10 value 94.664289 iter 20 value 87.979684 iter 30 value 85.559035 iter 40 value 85.049641 iter 50 value 85.001462 iter 60 value 84.964878 iter 70 value 84.874520 iter 80 value 84.527136 iter 90 value 83.391149 iter 100 value 83.183144 final value 83.183144 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 104.212313 iter 10 value 94.849835 iter 20 value 94.425751 iter 30 value 86.078843 iter 40 value 85.766704 iter 50 value 83.426998 iter 60 value 81.589389 iter 70 value 81.220774 iter 80 value 81.073010 iter 90 value 80.952527 iter 100 value 80.636921 final value 80.636921 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 115.631867 iter 10 value 94.609987 iter 20 value 94.100841 iter 30 value 93.301176 iter 40 value 86.219539 iter 50 value 85.083103 iter 60 value 83.487489 iter 70 value 82.480372 iter 80 value 81.791559 iter 90 value 81.215116 iter 100 value 80.981907 final value 80.981907 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 110.487380 iter 10 value 94.390046 iter 20 value 86.967687 iter 30 value 85.760668 iter 40 value 85.587312 iter 50 value 85.232956 iter 60 value 84.944523 iter 70 value 84.696476 iter 80 value 83.583927 iter 90 value 82.467735 iter 100 value 81.772309 final value 81.772309 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 111.946532 iter 10 value 94.599399 iter 20 value 93.629735 iter 30 value 87.149715 iter 40 value 84.332573 iter 50 value 83.259047 iter 60 value 82.509119 iter 70 value 82.217608 iter 80 value 82.042965 iter 90 value 81.957555 iter 100 value 81.932277 final value 81.932277 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 128.984058 iter 10 value 96.112893 iter 20 value 91.108875 iter 30 value 88.210679 iter 40 value 82.937920 iter 50 value 81.749016 iter 60 value 81.052139 iter 70 value 80.641805 iter 80 value 80.499100 iter 90 value 80.451678 iter 100 value 80.351126 final value 80.351126 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 117.757324 iter 10 value 99.135910 iter 20 value 91.311104 iter 30 value 86.113474 iter 40 value 84.616692 iter 50 value 82.605573 iter 60 value 82.158033 iter 70 value 81.667549 iter 80 value 80.847714 iter 90 value 80.672214 iter 100 value 80.560067 final value 80.560067 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 120.373131 iter 10 value 104.069477 iter 20 value 97.486063 iter 30 value 92.142517 iter 40 value 86.415841 iter 50 value 84.201105 iter 60 value 84.018394 iter 70 value 83.729403 iter 80 value 82.265871 iter 90 value 81.679944 iter 100 value 81.040560 final value 81.040560 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 104.508495 final value 94.485728 converged Fitting Repeat 2 # weights: 103 initial value 96.218112 final value 94.486079 converged Fitting Repeat 3 # weights: 103 initial value 110.504624 final value 94.468457 converged Fitting Repeat 4 # weights: 103 initial value 99.208633 final value 94.485722 converged Fitting Repeat 5 # weights: 103 initial value 98.903223 final value 94.487093 converged Fitting Repeat 1 # weights: 305 initial value 102.027224 iter 10 value 94.488684 iter 20 value 93.947587 final value 93.637749 converged Fitting Repeat 2 # weights: 305 initial value 101.443728 iter 10 value 94.471638 iter 20 value 93.940120 iter 30 value 90.778619 iter 40 value 90.778323 iter 50 value 89.782105 iter 60 value 85.194505 iter 70 value 85.192645 final value 85.192634 converged Fitting Repeat 3 # weights: 305 initial value 98.369117 iter 10 value 93.879733 iter 20 value 93.872780 iter 30 value 92.905789 final value 92.736354 converged Fitting Repeat 4 # weights: 305 initial value 101.755097 iter 10 value 94.488622 iter 20 value 94.483343 iter 30 value 93.583506 final value 93.573255 converged Fitting Repeat 5 # weights: 305 initial value 101.782828 iter 10 value 94.453300 iter 20 value 94.243915 iter 30 value 89.679811 iter 40 value 89.320291 iter 50 value 87.049079 iter 60 value 82.731839 iter 70 value 82.509197 iter 80 value 82.499109 iter 90 value 82.498064 iter 100 value 82.495983 final value 82.495983 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 105.278903 iter 10 value 94.492222 iter 20 value 94.445440 iter 30 value 89.268967 iter 40 value 88.942872 iter 50 value 88.501878 iter 60 value 81.791575 iter 70 value 81.510464 iter 80 value 81.504426 final value 81.504207 converged Fitting Repeat 2 # weights: 507 initial value 99.878130 iter 10 value 94.475111 iter 20 value 94.472112 iter 30 value 94.471802 iter 40 value 94.020863 iter 50 value 90.981290 iter 60 value 86.375283 iter 70 value 85.909593 iter 80 value 85.550245 iter 90 value 84.631398 iter 100 value 84.277791 final value 84.277791 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 120.789425 iter 10 value 94.476327 iter 20 value 94.469125 iter 30 value 90.526495 final value 90.474546 converged Fitting Repeat 4 # weights: 507 initial value 118.372235 iter 10 value 93.880485 iter 20 value 93.751740 iter 30 value 93.574100 iter 40 value 93.572984 iter 50 value 93.572497 iter 50 value 93.572497 final value 93.572497 converged Fitting Repeat 5 # weights: 507 initial value 123.641710 iter 10 value 94.475454 iter 20 value 94.430232 iter 30 value 93.877601 iter 40 value 93.741720 final value 93.573039 converged Fitting Repeat 1 # weights: 507 initial value 131.730859 iter 10 value 117.766968 iter 20 value 117.604604 iter 30 value 107.400842 iter 40 value 106.856329 iter 50 value 106.832937 final value 106.832920 converged Fitting Repeat 2 # weights: 507 initial value 118.836371 iter 10 value 117.688065 iter 20 value 117.545373 iter 30 value 117.542831 iter 40 value 117.501849 iter 50 value 116.670422 iter 60 value 110.887660 iter 70 value 106.857813 iter 80 value 106.663483 iter 90 value 106.629656 final value 106.629560 converged Fitting Repeat 3 # weights: 507 initial value 122.542444 iter 10 value 117.766857 iter 20 value 117.760456 iter 30 value 117.599307 iter 40 value 117.595608 final value 117.595576 converged Fitting Repeat 4 # weights: 507 initial value 130.756820 iter 10 value 115.263297 iter 20 value 109.041872 iter 30 value 106.979681 iter 40 value 106.832379 iter 50 value 106.829947 iter 60 value 106.402399 iter 70 value 106.077435 iter 80 value 106.070706 final value 106.070620 converged Fitting Repeat 5 # weights: 507 initial value 131.812196 iter 10 value 117.507580 iter 20 value 117.500350 iter 30 value 117.499768 iter 40 value 113.354119 iter 50 value 108.396441 iter 60 value 104.704573 iter 70 value 103.907558 iter 80 value 103.901701 iter 90 value 103.409389 iter 100 value 102.604225 final value 102.604225 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 -- Mon Mar 17 07:28:59 2025 *********************************************** 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 53.521 1.333 143.123
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 37.316 | 0.248 | 37.637 | |
FreqInteractors | 0.281 | 0.012 | 0.294 | |
calculateAAC | 0.038 | 0.008 | 0.046 | |
calculateAutocor | 0.677 | 0.028 | 0.707 | |
calculateCTDC | 0.093 | 0.000 | 0.093 | |
calculateCTDD | 0.749 | 0.000 | 0.751 | |
calculateCTDT | 0.262 | 0.004 | 0.266 | |
calculateCTriad | 0.469 | 0.004 | 0.474 | |
calculateDC | 0.131 | 0.000 | 0.131 | |
calculateF | 0.440 | 0.000 | 0.442 | |
calculateKSAAP | 0.144 | 0.000 | 0.143 | |
calculateQD_Sm | 2.369 | 0.036 | 2.409 | |
calculateTC | 2.443 | 0.028 | 2.476 | |
calculateTC_Sm | 0.332 | 0.000 | 0.332 | |
corr_plot | 37.730 | 0.024 | 37.973 | |
enrichfindP | 0.530 | 0.035 | 19.302 | |
enrichfind_hp | 0.066 | 0.028 | 1.413 | |
enrichplot | 0.512 | 0.008 | 0.522 | |
filter_missing_values | 0.001 | 0.000 | 0.002 | |
getFASTA | 0.127 | 0.012 | 5.762 | |
getHPI | 0.000 | 0.000 | 0.001 | |
get_negativePPI | 0.001 | 0.001 | 0.002 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0.000 | 0.002 | 0.001 | |
plotPPI | 0.073 | 0.012 | 0.085 | |
pred_ensembel | 18.327 | 0.513 | 17.883 | |
var_imp | 39.318 | 0.459 | 39.846 | |