Back to Multiple platform build/check report for BioC 3.21: simplified long |
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This page was generated on 2025-10-06 11:41 -0400 (Mon, 06 Oct 2025).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4832 |
merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4613 |
kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4554 |
kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4585 |
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 997/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.14.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | ERROR | skipped | |||||||||
merida1 | macOS 12.7.5 Monterey / x86_64 | OK | ERROR | skipped | skipped | |||||||||
kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | ERROR | skipped | skipped | |||||||||
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: 1.14.0 |
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_1.14.0.tar.gz |
StartedAt: 2025-10-03 10:18:10 -0000 (Fri, 03 Oct 2025) |
EndedAt: 2025-10-03 10:24:55 -0000 (Fri, 03 Oct 2025) |
EllapsedTime: 404.4 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_1.14.0.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 ‘1.14.0’ * 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 39.682 0.355 40.118 FSmethod 37.377 0.563 38.021 corr_plot 37.056 0.236 37.335 pred_ensembel 18.648 0.515 17.991 enrichfindP 0.497 0.028 18.831 getFASTA 0.076 0.028 7.741 * 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 ‘1.14.0’ ** 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 103.362733 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 101.071092 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 95.715975 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 101.736694 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 106.195829 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 119.178912 iter 10 value 93.892643 iter 20 value 93.871516 iter 20 value 93.871516 iter 20 value 93.871516 final value 93.871516 converged Fitting Repeat 2 # weights: 305 initial value 95.861238 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 98.390611 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 104.681189 iter 10 value 92.667685 iter 20 value 92.029306 iter 30 value 86.674387 iter 40 value 85.878934 final value 85.841270 converged Fitting Repeat 5 # weights: 305 initial value 97.387190 final value 94.354396 converged Fitting Repeat 1 # weights: 507 initial value 104.846365 iter 10 value 83.519641 iter 20 value 81.131807 iter 30 value 81.121651 final value 81.120873 converged Fitting Repeat 2 # weights: 507 initial value 98.330728 iter 10 value 93.929746 iter 20 value 92.512382 final value 92.512353 converged Fitting Repeat 3 # weights: 507 initial value 95.801817 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 118.796927 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 119.046832 iter 10 value 93.205814 iter 10 value 93.205814 iter 10 value 93.205814 final value 93.205814 converged Fitting Repeat 1 # weights: 103 initial value 96.370799 iter 10 value 93.140561 iter 20 value 89.414505 iter 30 value 89.199207 iter 40 value 89.122140 iter 50 value 89.120063 iter 50 value 89.120063 iter 50 value 89.120063 final value 89.120063 converged Fitting Repeat 2 # weights: 103 initial value 98.913298 iter 10 value 94.488795 iter 20 value 94.455186 iter 30 value 94.389525 iter 40 value 94.383482 iter 50 value 94.005393 iter 60 value 85.366216 iter 70 value 84.601658 iter 80 value 82.696921 iter 90 value 81.752308 iter 100 value 81.114011 final value 81.114011 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 98.493383 iter 10 value 92.524263 iter 20 value 88.926312 iter 30 value 85.856920 iter 40 value 85.571031 iter 50 value 83.042006 iter 60 value 82.335103 iter 70 value 82.277874 iter 80 value 82.233923 final value 82.232219 converged Fitting Repeat 4 # weights: 103 initial value 97.669504 iter 10 value 94.488553 iter 20 value 93.505203 iter 30 value 93.492507 iter 40 value 85.221551 iter 50 value 84.125052 iter 60 value 82.465433 iter 70 value 81.872843 iter 80 value 81.731741 iter 90 value 81.705031 final value 81.704165 converged Fitting Repeat 5 # weights: 103 initial value 108.632956 iter 10 value 94.487277 iter 20 value 93.963339 iter 30 value 93.823778 iter 40 value 84.635573 iter 50 value 83.230580 iter 60 value 82.945802 iter 70 value 81.032127 iter 80 value 80.790743 iter 90 value 80.767977 final value 80.767746 converged Fitting Repeat 1 # weights: 305 initial value 109.159280 iter 10 value 94.467508 iter 20 value 93.788507 iter 30 value 86.179068 iter 40 value 82.987346 iter 50 value 79.603940 iter 60 value 78.916217 iter 70 value 78.452299 iter 80 value 78.208950 iter 90 value 77.821306 iter 100 value 77.568428 final value 77.568428 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 126.494539 iter 10 value 94.525306 iter 20 value 93.947667 iter 30 value 92.807098 iter 40 value 82.290574 iter 50 value 80.265849 iter 60 value 78.697935 iter 70 value 78.000227 iter 80 value 77.859216 iter 90 value 77.442254 iter 100 value 77.189376 final value 77.189376 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.793498 iter 10 value 94.230092 iter 20 value 86.131490 iter 30 value 84.315411 iter 40 value 83.059720 iter 50 value 82.094885 iter 60 value 81.170502 iter 70 value 79.351775 iter 80 value 77.601797 iter 90 value 76.766788 iter 100 value 76.483563 final value 76.483563 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 115.205472 iter 10 value 94.902266 iter 20 value 94.476118 iter 30 value 91.694842 iter 40 value 88.847803 iter 50 value 87.906604 iter 60 value 86.249669 iter 70 value 79.877916 iter 80 value 78.189445 iter 90 value 77.719539 iter 100 value 77.315337 final value 77.315337 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.879005 iter 10 value 87.620739 iter 20 value 82.994603 iter 30 value 81.929303 iter 40 value 81.687620 iter 50 value 80.536011 iter 60 value 80.139562 iter 70 value 78.721805 iter 80 value 77.902257 iter 90 value 77.192352 iter 100 value 76.978883 final value 76.978883 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 112.198258 iter 10 value 94.257660 iter 20 value 92.964070 iter 30 value 90.336038 iter 40 value 83.785256 iter 50 value 80.427615 iter 60 value 78.089524 iter 70 value 77.683974 iter 80 value 76.980703 iter 90 value 76.793313 iter 100 value 76.645645 final value 76.645645 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 105.065446 iter 10 value 93.379552 iter 20 value 84.066897 iter 30 value 80.642497 iter 40 value 79.718218 iter 50 value 79.241110 iter 60 value 77.067022 iter 70 value 76.178450 iter 80 value 75.949878 iter 90 value 75.670963 iter 100 value 75.615215 final value 75.615215 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 122.070292 iter 10 value 93.762144 iter 20 value 88.249051 iter 30 value 85.040825 iter 40 value 82.895047 iter 50 value 82.444081 iter 60 value 80.629014 iter 70 value 77.971514 iter 80 value 77.211114 iter 90 value 77.013539 iter 100 value 76.743143 final value 76.743143 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 108.939156 iter 10 value 95.013297 iter 20 value 84.173209 iter 30 value 83.960950 iter 40 value 82.446223 iter 50 value 80.728259 iter 60 value 79.537579 iter 70 value 79.190373 iter 80 value 78.705120 iter 90 value 78.667231 iter 100 value 78.569168 final value 78.569168 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 103.219035 iter 10 value 93.717824 iter 20 value 85.202766 iter 30 value 82.688731 iter 40 value 82.153671 iter 50 value 81.868331 iter 60 value 81.028267 iter 70 value 80.670965 iter 80 value 80.393916 iter 90 value 79.240267 iter 100 value 78.029928 final value 78.029928 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.821643 final value 94.487234 converged Fitting Repeat 2 # weights: 103 initial value 99.608536 final value 94.485982 converged Fitting Repeat 3 # weights: 103 initial value 99.219416 iter 10 value 94.485835 iter 20 value 94.477124 iter 30 value 82.692525 iter 40 value 82.632396 iter 50 value 82.605794 iter 60 value 82.602609 iter 70 value 82.599929 iter 80 value 82.585556 iter 90 value 82.479107 iter 100 value 82.478491 final value 82.478491 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 101.690917 final value 94.487188 converged Fitting Repeat 5 # weights: 103 initial value 97.791941 final value 94.485931 converged Fitting Repeat 1 # weights: 305 initial value 104.139030 iter 10 value 94.489567 iter 20 value 94.484268 final value 94.484264 converged Fitting Repeat 2 # weights: 305 initial value 105.868038 iter 10 value 94.489262 iter 20 value 94.256674 iter 30 value 83.956613 iter 40 value 83.267549 iter 50 value 83.262352 iter 60 value 83.261870 iter 70 value 83.016443 iter 80 value 79.326425 iter 90 value 78.039614 iter 100 value 78.038495 final value 78.038495 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 115.393448 iter 10 value 93.304964 final value 93.304777 converged Fitting Repeat 4 # weights: 305 initial value 116.123607 iter 10 value 93.626502 iter 20 value 93.625724 iter 30 value 92.553815 iter 40 value 92.545392 iter 40 value 92.545392 iter 40 value 92.545392 final value 92.545392 converged Fitting Repeat 5 # weights: 305 initial value 110.444677 iter 10 value 93.305752 iter 20 value 93.302685 iter 30 value 81.445219 iter 40 value 81.441569 iter 50 value 81.092758 iter 60 value 81.046409 final value 81.045729 converged Fitting Repeat 1 # weights: 507 initial value 103.374009 iter 10 value 94.488190 iter 20 value 82.276170 iter 30 value 81.118570 final value 81.118282 converged Fitting Repeat 2 # weights: 507 initial value 102.388436 iter 10 value 94.363017 iter 20 value 94.357314 iter 30 value 94.353138 iter 40 value 89.453698 iter 50 value 89.064027 final value 89.063620 converged Fitting Repeat 3 # weights: 507 initial value 114.433650 iter 10 value 93.818375 iter 20 value 93.815369 iter 30 value 93.787531 iter 40 value 93.781346 iter 50 value 93.689111 iter 60 value 93.687574 iter 70 value 93.445540 iter 80 value 77.541234 iter 90 value 75.013319 iter 100 value 74.484517 final value 74.484517 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 96.706173 iter 10 value 93.781507 iter 20 value 93.779744 iter 30 value 93.701828 iter 40 value 93.700894 iter 50 value 93.686619 iter 60 value 93.536216 final value 93.536171 converged Fitting Repeat 5 # weights: 507 initial value 96.932317 iter 10 value 92.299877 iter 20 value 80.467227 iter 30 value 79.470079 iter 40 value 79.089480 iter 50 value 78.330302 iter 60 value 76.762639 iter 70 value 76.292551 iter 80 value 76.186757 iter 90 value 76.184590 final value 76.183036 converged Fitting Repeat 1 # weights: 103 initial value 103.174086 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 107.916352 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 112.586932 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 99.735188 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 110.189435 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 103.798178 final value 94.484208 converged Fitting Repeat 2 # weights: 305 initial value 99.669425 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 102.612952 final value 93.783647 converged Fitting Repeat 4 # weights: 305 initial value 106.567259 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 106.156498 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 99.713090 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 123.891778 iter 10 value 94.012863 iter 20 value 94.008781 final value 94.008684 converged Fitting Repeat 3 # weights: 507 initial value 101.065727 iter 10 value 94.475796 final value 94.026542 converged Fitting Repeat 4 # weights: 507 initial value 105.839279 final value 93.783647 converged Fitting Repeat 5 # weights: 507 initial value 98.684824 iter 10 value 94.144793 final value 94.144496 converged Fitting Repeat 1 # weights: 103 initial value 102.130994 iter 10 value 94.177208 iter 20 value 93.309049 iter 30 value 85.408313 iter 40 value 82.775980 iter 50 value 82.395554 iter 60 value 81.798748 iter 70 value 80.885740 iter 80 value 80.558706 iter 90 value 80.508664 final value 80.508635 converged Fitting Repeat 2 # weights: 103 initial value 97.098919 iter 10 value 94.469298 iter 20 value 94.240788 iter 30 value 94.219913 iter 40 value 94.177398 iter 50 value 90.248226 iter 60 value 84.257472 iter 70 value 83.861508 iter 80 value 83.782123 iter 90 value 82.859807 iter 100 value 82.423475 final value 82.423475 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 99.340551 iter 10 value 94.489012 iter 20 value 94.488591 iter 30 value 94.306029 iter 40 value 93.853749 iter 50 value 90.320273 iter 60 value 88.455702 iter 70 value 87.070671 iter 80 value 83.586178 iter 90 value 80.863743 iter 100 value 80.633578 final value 80.633578 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 105.394985 iter 10 value 94.493904 iter 20 value 94.346285 iter 30 value 94.094035 iter 40 value 94.092558 iter 50 value 94.092044 final value 94.091465 converged Fitting Repeat 5 # weights: 103 initial value 97.907046 iter 10 value 94.599055 iter 20 value 94.486498 iter 30 value 93.071153 iter 40 value 90.649099 iter 50 value 87.642655 iter 60 value 82.901746 iter 70 value 80.711949 iter 80 value 80.241499 iter 90 value 80.192230 final value 80.192208 converged Fitting Repeat 1 # weights: 305 initial value 101.673068 iter 10 value 93.264934 iter 20 value 82.970345 iter 30 value 81.738597 iter 40 value 81.462569 iter 50 value 80.057272 iter 60 value 79.312492 iter 70 value 79.052063 iter 80 value 78.812164 iter 90 value 78.654883 iter 100 value 78.588510 final value 78.588510 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 104.324808 iter 10 value 93.277587 iter 20 value 84.118098 iter 30 value 83.116760 iter 40 value 82.596407 iter 50 value 82.351207 iter 60 value 81.511632 iter 70 value 80.488852 iter 80 value 80.174060 iter 90 value 79.722541 iter 100 value 79.518421 final value 79.518421 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 102.571782 iter 10 value 94.405463 iter 20 value 94.222671 iter 30 value 86.258519 iter 40 value 84.338623 iter 50 value 83.471065 iter 60 value 82.597589 iter 70 value 82.530761 iter 80 value 82.478783 iter 90 value 81.690403 iter 100 value 79.968768 final value 79.968768 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 124.044462 iter 10 value 94.543867 iter 20 value 94.123816 iter 30 value 92.684488 iter 40 value 84.284734 iter 50 value 82.305662 iter 60 value 81.045233 iter 70 value 80.670330 iter 80 value 80.568222 iter 90 value 80.501685 iter 100 value 80.431153 final value 80.431153 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 99.185437 iter 10 value 94.304980 iter 20 value 83.660225 iter 30 value 82.377059 iter 40 value 81.005891 iter 50 value 80.230133 iter 60 value 80.070815 iter 70 value 80.051677 iter 80 value 80.049181 iter 90 value 80.041995 iter 100 value 79.748058 final value 79.748058 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 108.374809 iter 10 value 98.921761 iter 20 value 92.713443 iter 30 value 85.858947 iter 40 value 84.146091 iter 50 value 83.016322 iter 60 value 81.621616 iter 70 value 79.632557 iter 80 value 79.462002 iter 90 value 79.237939 iter 100 value 79.197770 final value 79.197770 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 125.829331 iter 10 value 94.220517 iter 20 value 88.048782 iter 30 value 84.300249 iter 40 value 83.140082 iter 50 value 82.548177 iter 60 value 81.024159 iter 70 value 80.470366 iter 80 value 80.279517 iter 90 value 80.230308 iter 100 value 80.136512 final value 80.136512 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 114.257943 iter 10 value 94.468811 iter 20 value 88.913967 iter 30 value 85.019124 iter 40 value 83.428732 iter 50 value 82.945674 iter 60 value 82.301089 iter 70 value 80.071664 iter 80 value 79.547359 iter 90 value 79.213769 iter 100 value 79.054647 final value 79.054647 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 112.017162 iter 10 value 94.650281 iter 20 value 94.379006 iter 30 value 94.138562 iter 40 value 94.082122 iter 50 value 84.460548 iter 60 value 84.207906 iter 70 value 83.761297 iter 80 value 82.310004 iter 90 value 81.068424 iter 100 value 80.104842 final value 80.104842 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 110.362723 iter 10 value 97.715437 iter 20 value 96.687137 iter 30 value 94.074329 iter 40 value 86.563028 iter 50 value 84.494109 iter 60 value 83.475761 iter 70 value 82.601982 iter 80 value 82.090561 iter 90 value 81.289722 iter 100 value 80.226297 final value 80.226297 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.210425 final value 94.215600 converged Fitting Repeat 2 # weights: 103 initial value 99.829297 final value 94.485713 converged Fitting Repeat 3 # weights: 103 initial value 101.060787 iter 10 value 94.486071 iter 10 value 94.486070 iter 10 value 94.486070 final value 94.486070 converged Fitting Repeat 4 # weights: 103 initial value 107.961960 final value 94.485815 converged Fitting Repeat 5 # weights: 103 initial value 101.526956 iter 10 value 94.485783 iter 20 value 94.479027 iter 30 value 94.028757 iter 40 value 94.027801 iter 50 value 94.026665 iter 60 value 93.277231 iter 70 value 84.863658 iter 80 value 84.861217 iter 90 value 84.566036 iter 100 value 84.563466 final value 84.563466 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 94.753352 iter 10 value 94.031490 iter 20 value 94.024709 iter 30 value 86.058831 iter 40 value 85.790091 iter 50 value 83.675750 iter 60 value 83.505018 iter 70 value 83.347248 iter 80 value 83.136344 final value 83.132127 converged Fitting Repeat 2 # weights: 305 initial value 100.328640 iter 10 value 94.489144 iter 20 value 94.484649 final value 94.484646 converged Fitting Repeat 3 # weights: 305 initial value 115.340608 iter 10 value 94.257701 iter 20 value 94.220831 iter 30 value 94.083023 final value 93.990132 converged Fitting Repeat 4 # weights: 305 initial value 108.313099 iter 10 value 94.101845 iter 20 value 93.939022 iter 30 value 92.936873 iter 40 value 88.963465 iter 50 value 87.890254 final value 87.889861 converged Fitting Repeat 5 # weights: 305 initial value 102.284745 iter 10 value 94.489499 iter 20 value 94.389803 final value 94.027280 converged Fitting Repeat 1 # weights: 507 initial value 121.451691 iter 10 value 94.492448 iter 20 value 94.458673 iter 30 value 83.941587 iter 40 value 83.334041 iter 50 value 82.069876 iter 60 value 80.356384 iter 70 value 79.443923 iter 80 value 79.383870 iter 90 value 79.378457 iter 100 value 79.052492 final value 79.052492 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 103.511874 iter 10 value 94.034944 iter 20 value 94.027388 iter 30 value 94.026815 final value 94.026771 converged Fitting Repeat 3 # weights: 507 initial value 97.672841 iter 10 value 94.034885 iter 20 value 93.383037 iter 30 value 83.535706 iter 40 value 83.473805 iter 50 value 83.275514 iter 60 value 83.275109 iter 70 value 83.273865 iter 80 value 83.249162 iter 90 value 82.676731 iter 100 value 82.461975 final value 82.461975 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 101.313111 iter 10 value 93.606603 iter 20 value 93.581180 iter 30 value 85.269502 iter 40 value 84.818278 iter 50 value 84.817143 iter 60 value 84.816106 iter 70 value 84.292246 iter 80 value 80.726631 iter 90 value 80.530756 iter 100 value 80.528951 final value 80.528951 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 107.001929 iter 10 value 94.482623 iter 20 value 94.287897 iter 30 value 94.280943 iter 40 value 94.279837 iter 50 value 94.100549 iter 60 value 93.881559 iter 70 value 93.594601 iter 80 value 93.384065 iter 90 value 93.364292 iter 100 value 93.362000 final value 93.362000 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.952621 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 95.949247 final value 94.482478 converged Fitting Repeat 3 # weights: 103 initial value 100.599279 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 101.906931 iter 10 value 86.625332 final value 86.622126 converged Fitting Repeat 5 # weights: 103 initial value 96.204779 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 107.688996 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 99.854898 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 96.485379 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 94.994836 iter 10 value 86.284266 iter 20 value 85.932647 final value 85.932643 converged Fitting Repeat 5 # weights: 305 initial value 107.288255 iter 10 value 87.512927 iter 20 value 85.828500 iter 30 value 83.870210 iter 40 value 83.845060 iter 50 value 83.583533 iter 60 value 83.464918 final value 83.464842 converged Fitting Repeat 1 # weights: 507 initial value 116.251411 iter 10 value 94.484208 iter 10 value 94.484208 final value 94.484208 converged Fitting Repeat 2 # weights: 507 initial value 105.204007 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 103.294503 iter 10 value 94.476191 iter 10 value 94.476191 iter 10 value 94.476191 final value 94.476191 converged Fitting Repeat 4 # weights: 507 initial value 106.260009 final value 94.264858 converged Fitting Repeat 5 # weights: 507 initial value 113.713682 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 103.723029 iter 10 value 94.486256 iter 20 value 87.531117 iter 30 value 87.012297 iter 40 value 86.728237 iter 50 value 86.667848 iter 60 value 84.761747 iter 70 value 84.715188 iter 80 value 84.686243 iter 90 value 84.671445 final value 84.670805 converged Fitting Repeat 2 # weights: 103 initial value 101.682780 iter 10 value 94.467540 iter 20 value 93.965224 iter 30 value 93.779932 iter 40 value 93.026766 iter 50 value 92.313710 iter 60 value 86.395936 iter 70 value 85.141969 iter 80 value 84.756585 iter 90 value 84.337534 iter 100 value 83.768780 final value 83.768780 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 96.758315 iter 10 value 94.491685 iter 20 value 94.304482 iter 30 value 89.934880 iter 40 value 85.333038 iter 50 value 84.823471 iter 60 value 84.816426 iter 70 value 84.816279 iter 70 value 84.816279 iter 70 value 84.816279 final value 84.816279 converged Fitting Repeat 4 # weights: 103 initial value 99.928191 iter 10 value 94.481737 iter 20 value 94.035315 iter 30 value 92.438306 iter 40 value 84.915064 iter 50 value 84.498579 iter 60 value 84.107066 iter 70 value 83.815611 iter 80 value 83.710848 final value 83.710726 converged Fitting Repeat 5 # weights: 103 initial value 101.712858 iter 10 value 94.488572 iter 20 value 94.330904 iter 30 value 89.316026 iter 40 value 85.624984 iter 50 value 85.348058 iter 60 value 85.281829 iter 70 value 85.240750 iter 80 value 85.223128 final value 85.222572 converged Fitting Repeat 1 # weights: 305 initial value 101.377589 iter 10 value 94.534469 iter 20 value 94.408580 iter 30 value 93.190538 iter 40 value 90.876775 iter 50 value 87.041491 iter 60 value 85.339263 iter 70 value 84.126473 iter 80 value 83.124288 iter 90 value 83.052801 iter 100 value 82.942566 final value 82.942566 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 108.863464 iter 10 value 94.233080 iter 20 value 87.040411 iter 30 value 86.013145 iter 40 value 85.081137 iter 50 value 84.945495 iter 60 value 84.781123 iter 70 value 83.999632 iter 80 value 82.884140 iter 90 value 82.642298 iter 100 value 82.331236 final value 82.331236 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 104.151643 iter 10 value 94.554867 iter 20 value 89.722494 iter 30 value 87.786252 iter 40 value 87.119778 iter 50 value 86.389427 iter 60 value 85.100538 iter 70 value 84.990334 iter 80 value 84.937643 iter 90 value 84.272043 iter 100 value 82.589278 final value 82.589278 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 119.724769 iter 10 value 94.589383 iter 20 value 92.154081 iter 30 value 89.783792 iter 40 value 88.102256 iter 50 value 84.181121 iter 60 value 83.347146 iter 70 value 82.933217 iter 80 value 82.709152 iter 90 value 82.586130 iter 100 value 82.573870 final value 82.573870 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 108.453801 iter 10 value 94.497591 iter 20 value 94.270046 iter 30 value 93.745395 iter 40 value 85.957447 iter 50 value 85.712228 iter 60 value 85.499196 iter 70 value 83.646630 iter 80 value 83.462169 iter 90 value 82.711905 iter 100 value 82.247254 final value 82.247254 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 109.645390 iter 10 value 94.490919 iter 20 value 93.678179 iter 30 value 91.472008 iter 40 value 88.998733 iter 50 value 84.293996 iter 60 value 82.787897 iter 70 value 81.970593 iter 80 value 81.898391 iter 90 value 81.886994 iter 100 value 81.828838 final value 81.828838 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 104.697276 iter 10 value 94.605278 iter 20 value 93.858687 iter 30 value 88.339757 iter 40 value 86.218730 iter 50 value 84.269998 iter 60 value 83.511930 iter 70 value 83.031698 iter 80 value 82.063700 iter 90 value 81.676752 iter 100 value 81.443000 final value 81.443000 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 119.312037 iter 10 value 94.458294 iter 20 value 90.260223 iter 30 value 88.211342 iter 40 value 87.382706 iter 50 value 84.688615 iter 60 value 83.785592 iter 70 value 83.032484 iter 80 value 82.509914 iter 90 value 82.396371 iter 100 value 82.254597 final value 82.254597 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.512117 iter 10 value 94.433689 iter 20 value 93.170826 iter 30 value 88.124620 iter 40 value 85.961862 iter 50 value 84.756624 iter 60 value 83.971501 iter 70 value 83.586001 iter 80 value 82.857672 iter 90 value 82.245146 iter 100 value 81.825640 final value 81.825640 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 106.778308 iter 10 value 94.463859 iter 20 value 92.935533 iter 30 value 90.231065 iter 40 value 89.106900 iter 50 value 86.068782 iter 60 value 85.688665 iter 70 value 85.108373 iter 80 value 84.655973 iter 90 value 84.451981 iter 100 value 84.337274 final value 84.337274 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 101.282179 final value 94.485757 converged Fitting Repeat 2 # weights: 103 initial value 98.290768 final value 94.485688 converged Fitting Repeat 3 # weights: 103 initial value 96.979357 final value 94.485943 converged Fitting Repeat 4 # weights: 103 initial value 96.466334 iter 10 value 94.471747 iter 20 value 94.468476 iter 30 value 94.467093 final value 94.466855 converged Fitting Repeat 5 # weights: 103 initial value 106.318548 final value 94.485802 converged Fitting Repeat 1 # weights: 305 initial value 100.092241 iter 10 value 94.488963 iter 20 value 86.186499 final value 85.937821 converged Fitting Repeat 2 # weights: 305 initial value 98.269630 iter 10 value 94.489171 iter 20 value 94.346692 iter 30 value 88.628589 iter 40 value 87.941611 iter 50 value 85.963490 iter 60 value 85.959622 iter 70 value 85.953400 iter 80 value 85.949478 iter 90 value 85.759422 iter 100 value 83.510040 final value 83.510040 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 97.661645 iter 10 value 93.951264 iter 20 value 93.925436 iter 30 value 93.868064 iter 40 value 93.863324 iter 50 value 93.862691 iter 60 value 93.860493 final value 93.860450 converged Fitting Repeat 4 # weights: 305 initial value 98.812211 iter 10 value 94.488610 iter 20 value 94.421901 iter 30 value 85.940605 iter 40 value 85.933053 iter 50 value 85.932911 final value 85.932892 converged Fitting Repeat 5 # weights: 305 initial value 123.964171 iter 10 value 94.489055 iter 20 value 94.484357 iter 30 value 94.419774 iter 40 value 94.170233 iter 50 value 90.883626 iter 60 value 85.413277 iter 70 value 83.902716 iter 80 value 82.572511 iter 90 value 82.062600 iter 100 value 81.599830 final value 81.599830 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 123.826860 iter 10 value 94.492474 iter 20 value 94.430432 iter 30 value 89.442083 iter 40 value 84.201354 final value 84.191806 converged Fitting Repeat 2 # weights: 507 initial value 99.396691 iter 10 value 94.272971 iter 20 value 94.267624 iter 30 value 86.564726 iter 40 value 83.751928 iter 50 value 83.606867 iter 60 value 83.572156 iter 70 value 83.264073 iter 80 value 81.906957 iter 90 value 81.084144 iter 100 value 80.899871 final value 80.899871 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 95.151203 iter 10 value 94.487466 iter 20 value 89.869145 iter 30 value 87.794701 iter 40 value 87.234889 iter 50 value 87.231358 iter 60 value 87.230968 iter 70 value 87.102495 iter 80 value 87.072014 final value 87.071788 converged Fitting Repeat 4 # weights: 507 initial value 119.151553 iter 10 value 94.491748 iter 20 value 92.186155 iter 30 value 84.886584 iter 40 value 84.227983 final value 84.059577 converged Fitting Repeat 5 # weights: 507 initial value 96.440523 iter 10 value 94.260890 iter 20 value 91.636246 iter 30 value 88.014506 iter 40 value 87.846851 iter 50 value 87.845044 iter 60 value 87.787237 iter 70 value 87.783777 iter 80 value 87.782064 iter 90 value 87.780838 iter 90 value 87.780838 final value 87.780838 converged Fitting Repeat 1 # weights: 103 initial value 99.375253 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 94.069790 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 95.223957 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 100.314898 iter 10 value 93.733160 final value 93.732893 converged Fitting Repeat 5 # weights: 103 initial value 97.011400 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 96.839233 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 95.147398 iter 10 value 90.464626 iter 20 value 90.457006 iter 30 value 90.456951 final value 90.456939 converged Fitting Repeat 3 # weights: 305 initial value 111.862268 iter 10 value 92.102082 final value 91.506173 converged Fitting Repeat 4 # weights: 305 initial value 107.993324 final value 94.008696 converged Fitting Repeat 5 # weights: 305 initial value 104.634058 final value 94.008696 converged Fitting Repeat 1 # weights: 507 initial value 111.145521 iter 10 value 94.008691 final value 94.008679 converged Fitting Repeat 2 # weights: 507 initial value 110.162366 final value 94.052910 converged Fitting Repeat 3 # weights: 507 initial value 104.523128 iter 10 value 93.440660 iter 20 value 87.217897 iter 30 value 85.767753 iter 40 value 85.750155 iter 40 value 85.750154 iter 40 value 85.750154 final value 85.750154 converged Fitting Repeat 4 # weights: 507 initial value 102.708705 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 97.063086 iter 10 value 93.517209 iter 20 value 91.278424 iter 30 value 91.103212 iter 40 value 90.951185 iter 50 value 90.950592 iter 60 value 90.950233 iter 70 value 90.950082 iter 80 value 90.950024 final value 90.950006 converged Fitting Repeat 1 # weights: 103 initial value 96.635467 iter 10 value 94.050693 iter 20 value 89.756299 iter 30 value 87.229544 iter 40 value 86.629187 iter 50 value 84.253832 iter 60 value 83.898363 iter 70 value 83.834038 iter 80 value 83.092107 iter 90 value 82.929781 iter 100 value 82.716943 final value 82.716943 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 107.738167 iter 10 value 94.055584 iter 20 value 93.822073 iter 30 value 88.289405 iter 40 value 86.619289 iter 50 value 86.470800 iter 60 value 84.371909 iter 70 value 83.813350 iter 80 value 83.225258 iter 90 value 82.767190 iter 100 value 82.660221 final value 82.660221 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 98.178367 iter 10 value 94.067831 iter 20 value 94.056695 iter 30 value 88.243494 iter 40 value 86.651626 iter 50 value 86.277088 iter 60 value 85.718567 iter 70 value 84.144009 iter 80 value 83.933958 iter 90 value 83.662591 iter 100 value 83.109449 final value 83.109449 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 100.630061 iter 10 value 94.040321 iter 20 value 88.174577 iter 30 value 87.161983 iter 40 value 84.776493 iter 50 value 83.933920 iter 60 value 83.528347 iter 70 value 83.043645 iter 80 value 82.906104 iter 90 value 82.846999 iter 100 value 82.738797 final value 82.738797 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 97.312425 iter 10 value 94.062844 iter 20 value 94.013230 iter 30 value 93.820126 iter 40 value 93.804654 iter 50 value 87.059820 iter 60 value 86.563867 iter 70 value 86.133773 iter 80 value 85.595419 iter 90 value 85.424500 iter 100 value 83.611925 final value 83.611925 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 106.581570 iter 10 value 94.168652 iter 20 value 92.944173 iter 30 value 88.021259 iter 40 value 85.113709 iter 50 value 84.541436 iter 60 value 83.395692 iter 70 value 82.356557 iter 80 value 81.785926 iter 90 value 81.702994 iter 100 value 81.692116 final value 81.692116 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.518710 iter 10 value 94.096873 iter 20 value 92.121722 iter 30 value 89.011171 iter 40 value 88.659295 iter 50 value 88.269083 iter 60 value 86.563892 iter 70 value 83.228996 iter 80 value 83.022531 iter 90 value 82.756216 iter 100 value 82.578170 final value 82.578170 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 110.309333 iter 10 value 94.108620 iter 20 value 92.092053 iter 30 value 86.059264 iter 40 value 83.976880 iter 50 value 83.698261 iter 60 value 83.347300 iter 70 value 82.963413 iter 80 value 82.739843 iter 90 value 82.661928 iter 100 value 82.654557 final value 82.654557 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 113.072954 iter 10 value 94.013650 iter 20 value 87.035898 iter 30 value 85.691132 iter 40 value 85.217603 iter 50 value 83.678736 iter 60 value 82.389458 iter 70 value 81.887553 iter 80 value 81.777325 iter 90 value 81.699756 iter 100 value 81.574506 final value 81.574506 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 102.821101 iter 10 value 93.995785 iter 20 value 90.783702 iter 30 value 85.744170 iter 40 value 84.255764 iter 50 value 83.583333 iter 60 value 82.850500 iter 70 value 81.976152 iter 80 value 81.878080 iter 90 value 81.755198 iter 100 value 81.671740 final value 81.671740 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 122.564261 iter 10 value 93.819468 iter 20 value 90.303266 iter 30 value 87.415145 iter 40 value 83.822296 iter 50 value 83.678550 iter 60 value 83.588791 iter 70 value 83.422938 iter 80 value 82.936949 iter 90 value 82.544315 iter 100 value 82.458246 final value 82.458246 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 113.869396 iter 10 value 93.507716 iter 20 value 88.419726 iter 30 value 86.586841 iter 40 value 84.422101 iter 50 value 83.096856 iter 60 value 82.377670 iter 70 value 82.246626 iter 80 value 82.174986 iter 90 value 82.032869 iter 100 value 81.648166 final value 81.648166 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 119.399050 iter 10 value 94.638820 iter 20 value 92.462409 iter 30 value 87.745320 iter 40 value 86.217416 iter 50 value 84.294201 iter 60 value 83.127675 iter 70 value 82.798344 iter 80 value 82.267488 iter 90 value 81.859209 iter 100 value 81.824069 final value 81.824069 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 103.224622 iter 10 value 94.112169 iter 20 value 88.648416 iter 30 value 84.928697 iter 40 value 83.904820 iter 50 value 83.517257 iter 60 value 83.078337 iter 70 value 82.062049 iter 80 value 81.691877 iter 90 value 81.529525 iter 100 value 81.455669 final value 81.455669 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 105.267467 iter 10 value 96.192480 iter 20 value 88.122323 iter 30 value 87.054075 iter 40 value 85.831671 iter 50 value 85.429716 iter 60 value 84.828966 iter 70 value 84.185031 iter 80 value 83.821016 iter 90 value 83.610301 iter 100 value 82.962419 final value 82.962419 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.609467 final value 94.054695 converged Fitting Repeat 2 # weights: 103 initial value 107.763305 final value 94.054822 converged Fitting Repeat 3 # weights: 103 initial value 99.574817 final value 94.054556 converged Fitting Repeat 4 # weights: 103 initial value 100.369276 final value 94.054347 converged Fitting Repeat 5 # weights: 103 initial value 94.075616 final value 94.054469 converged Fitting Repeat 1 # weights: 305 initial value 111.462409 iter 10 value 94.058223 iter 20 value 93.750678 iter 30 value 85.316088 iter 40 value 84.804242 iter 50 value 84.653179 iter 60 value 84.022528 iter 70 value 84.017406 iter 80 value 84.000266 iter 90 value 83.997850 iter 100 value 83.800870 final value 83.800870 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 103.892368 iter 10 value 94.057608 iter 20 value 94.052960 iter 30 value 93.953636 iter 40 value 93.765195 iter 50 value 89.848025 iter 60 value 86.837790 iter 70 value 86.798552 iter 80 value 86.795467 final value 86.795405 converged Fitting Repeat 3 # weights: 305 initial value 100.060603 iter 10 value 94.013669 iter 20 value 93.888500 iter 30 value 93.794536 iter 40 value 93.785124 final value 93.785061 converged Fitting Repeat 4 # weights: 305 initial value 111.447599 iter 10 value 94.057956 iter 20 value 94.053259 iter 30 value 93.825879 final value 93.809342 converged Fitting Repeat 5 # weights: 305 initial value 98.828794 iter 10 value 94.057714 iter 20 value 94.052886 iter 30 value 93.873760 iter 40 value 84.785979 iter 50 value 84.669600 iter 60 value 84.623024 iter 70 value 84.583038 iter 80 value 84.196453 iter 90 value 84.059012 iter 100 value 83.819640 final value 83.819640 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 105.428433 iter 10 value 94.038950 iter 20 value 93.970732 iter 30 value 93.969599 final value 93.969505 converged Fitting Repeat 2 # weights: 507 initial value 102.481295 iter 10 value 93.819649 iter 20 value 93.764659 iter 30 value 93.761003 iter 40 value 93.758355 iter 50 value 93.757978 final value 93.756255 converged Fitting Repeat 3 # weights: 507 initial value 115.953664 iter 10 value 94.061215 iter 20 value 94.018853 iter 30 value 89.398492 iter 40 value 84.880203 iter 50 value 84.857016 final value 84.856990 converged Fitting Repeat 4 # weights: 507 initial value 121.478381 iter 10 value 94.016202 iter 20 value 94.011771 iter 30 value 91.566686 iter 40 value 91.565495 iter 50 value 90.473822 iter 60 value 90.459061 iter 70 value 90.458432 iter 80 value 90.457625 iter 90 value 90.445812 iter 100 value 90.372911 final value 90.372911 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 99.311187 iter 10 value 94.059711 iter 20 value 91.525269 iter 30 value 91.456051 iter 40 value 90.873837 iter 50 value 90.557221 final value 90.557216 converged Fitting Repeat 1 # weights: 103 initial value 95.300140 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 102.059148 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 99.739853 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 103.050505 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 96.413189 final value 94.008696 converged Fitting Repeat 1 # weights: 305 initial value 108.466260 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 96.783297 final value 94.033149 converged Fitting Repeat 3 # weights: 305 initial value 114.587256 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 102.185250 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 95.146590 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 94.568404 final value 94.008696 converged Fitting Repeat 2 # weights: 507 initial value 94.553603 iter 10 value 93.902092 final value 93.273743 converged Fitting Repeat 3 # weights: 507 initial value 97.215855 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 95.882919 iter 10 value 94.008697 final value 94.008696 converged Fitting Repeat 5 # weights: 507 initial value 96.206105 final value 94.008696 converged Fitting Repeat 1 # weights: 103 initial value 97.051779 iter 10 value 93.895070 iter 20 value 89.496149 iter 30 value 87.681967 iter 40 value 84.831360 iter 50 value 83.236440 iter 60 value 82.855974 iter 70 value 82.311678 iter 80 value 82.257427 iter 90 value 82.256251 iter 100 value 82.255792 final value 82.255792 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 96.656029 iter 10 value 93.980226 iter 20 value 88.621648 iter 30 value 85.799185 iter 40 value 84.493615 iter 50 value 83.347191 iter 60 value 82.772792 iter 70 value 82.644401 iter 80 value 82.402066 iter 90 value 82.262688 final value 82.255791 converged Fitting Repeat 3 # weights: 103 initial value 96.915921 iter 10 value 94.036658 iter 20 value 92.851686 iter 30 value 92.327034 iter 40 value 89.855252 iter 50 value 89.042536 iter 60 value 87.241502 iter 70 value 85.817717 iter 80 value 84.492703 iter 90 value 83.853150 iter 100 value 83.617725 final value 83.617725 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 102.667041 iter 10 value 93.978385 iter 20 value 87.586276 iter 30 value 86.504578 iter 40 value 86.428124 iter 50 value 85.824473 iter 60 value 84.578543 iter 70 value 83.572243 iter 80 value 82.656293 iter 90 value 82.462413 iter 100 value 82.364460 final value 82.364460 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 100.398038 iter 10 value 94.152893 iter 20 value 94.057046 iter 30 value 94.026666 iter 40 value 93.499569 iter 50 value 90.229271 iter 60 value 88.486773 iter 70 value 86.451390 iter 80 value 85.644013 iter 90 value 85.505745 iter 100 value 85.490117 final value 85.490117 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 114.517872 iter 10 value 94.047541 iter 20 value 93.417360 iter 30 value 92.864411 iter 40 value 88.788317 iter 50 value 86.677530 iter 60 value 85.117588 iter 70 value 84.265494 iter 80 value 82.693347 iter 90 value 82.218624 iter 100 value 81.861643 final value 81.861643 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 113.858534 iter 10 value 93.863534 iter 20 value 89.591312 iter 30 value 86.961334 iter 40 value 85.036861 iter 50 value 83.012902 iter 60 value 81.747891 iter 70 value 81.380884 iter 80 value 81.095327 iter 90 value 80.894626 iter 100 value 80.758751 final value 80.758751 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 103.213643 iter 10 value 94.071163 iter 20 value 93.311048 iter 30 value 89.048280 iter 40 value 87.736724 iter 50 value 86.909960 iter 60 value 84.184645 iter 70 value 82.550708 iter 80 value 82.237294 iter 90 value 81.469988 iter 100 value 81.187595 final value 81.187595 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 99.464116 iter 10 value 93.905898 iter 20 value 93.105696 iter 30 value 92.991177 iter 40 value 89.832001 iter 50 value 89.338911 iter 60 value 88.314627 iter 70 value 87.010294 iter 80 value 85.095920 iter 90 value 84.334406 iter 100 value 83.766114 final value 83.766114 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 112.312724 iter 10 value 94.003819 iter 20 value 91.565825 iter 30 value 87.265636 iter 40 value 84.642319 iter 50 value 82.599327 iter 60 value 81.868660 iter 70 value 81.346807 iter 80 value 81.135400 iter 90 value 80.986790 iter 100 value 80.950468 final value 80.950468 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 105.934956 iter 10 value 93.178858 iter 20 value 90.576066 iter 30 value 86.691200 iter 40 value 84.750145 iter 50 value 83.695485 iter 60 value 83.356234 iter 70 value 83.119213 iter 80 value 81.602246 iter 90 value 81.441893 iter 100 value 81.398885 final value 81.398885 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 139.239768 iter 10 value 94.033764 iter 20 value 88.232373 iter 30 value 86.048385 iter 40 value 83.798431 iter 50 value 82.091159 iter 60 value 81.474886 iter 70 value 81.118285 iter 80 value 80.960862 iter 90 value 80.915788 iter 100 value 80.877531 final value 80.877531 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 103.813159 iter 10 value 89.322467 iter 20 value 86.828401 iter 30 value 84.005841 iter 40 value 81.977195 iter 50 value 81.126883 iter 60 value 80.822642 iter 70 value 80.739684 iter 80 value 80.701373 iter 90 value 80.634435 iter 100 value 80.616125 final value 80.616125 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 113.454763 iter 10 value 93.923631 iter 20 value 92.516556 iter 30 value 88.894173 iter 40 value 85.688337 iter 50 value 83.880089 iter 60 value 83.596805 iter 70 value 81.452361 iter 80 value 81.184140 iter 90 value 81.019711 iter 100 value 80.858064 final value 80.858064 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 107.363026 iter 10 value 94.131309 iter 20 value 90.843935 iter 30 value 88.203813 iter 40 value 87.427399 iter 50 value 86.957266 iter 60 value 85.130805 iter 70 value 84.586149 iter 80 value 82.573699 iter 90 value 82.130533 iter 100 value 81.646925 final value 81.646925 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.971951 iter 10 value 94.010204 iter 20 value 93.935542 iter 30 value 87.902611 iter 40 value 87.557521 iter 50 value 87.501487 iter 60 value 87.383430 iter 70 value 87.339759 iter 80 value 86.635276 iter 90 value 86.634588 iter 100 value 86.634066 final value 86.634066 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 103.092930 final value 94.010191 converged Fitting Repeat 3 # weights: 103 initial value 95.926077 final value 94.054764 converged Fitting Repeat 4 # weights: 103 initial value 95.333573 final value 94.054338 converged Fitting Repeat 5 # weights: 103 initial value 103.813138 final value 94.054608 converged Fitting Repeat 1 # weights: 305 initial value 103.830105 iter 10 value 94.057779 iter 20 value 92.913585 iter 30 value 85.998517 iter 40 value 85.642721 final value 85.641644 converged Fitting Repeat 2 # weights: 305 initial value 100.003062 iter 10 value 94.055607 iter 20 value 93.703177 iter 30 value 90.149826 iter 40 value 89.672210 iter 50 value 89.670199 iter 60 value 89.314369 iter 70 value 89.285530 final value 89.285233 converged Fitting Repeat 3 # weights: 305 initial value 100.990015 iter 10 value 94.057353 iter 20 value 94.039537 iter 30 value 89.783997 iter 40 value 89.477349 iter 50 value 87.218972 iter 60 value 87.023820 iter 70 value 87.011826 iter 80 value 85.837223 iter 90 value 85.641651 final value 85.641493 converged Fitting Repeat 4 # weights: 305 initial value 115.686982 iter 10 value 94.057248 iter 20 value 94.042467 iter 30 value 87.253431 iter 40 value 86.383200 iter 50 value 86.377923 iter 60 value 84.354037 iter 70 value 83.984121 final value 83.984119 converged Fitting Repeat 5 # weights: 305 initial value 101.659112 iter 10 value 94.057393 iter 20 value 93.967584 iter 30 value 87.049461 iter 40 value 86.979120 iter 50 value 84.635567 iter 60 value 84.273073 final value 84.272941 converged Fitting Repeat 1 # weights: 507 initial value 108.075677 iter 10 value 93.993869 iter 20 value 93.987010 iter 30 value 87.852904 iter 40 value 86.431944 iter 50 value 86.154730 iter 60 value 85.668407 final value 85.667733 converged Fitting Repeat 2 # weights: 507 initial value 97.499598 iter 10 value 94.016896 iter 20 value 93.692528 iter 30 value 85.492401 iter 40 value 84.240721 iter 50 value 82.617906 iter 60 value 82.475739 iter 70 value 81.757916 iter 80 value 81.263739 iter 90 value 81.255012 iter 90 value 81.255011 iter 90 value 81.255011 final value 81.255011 converged Fitting Repeat 3 # weights: 507 initial value 122.578675 iter 10 value 94.062565 iter 20 value 94.053806 iter 30 value 93.842680 iter 40 value 87.817703 iter 50 value 87.512348 iter 60 value 87.505440 iter 70 value 86.037103 iter 80 value 84.671569 iter 90 value 84.669864 iter 100 value 84.668245 final value 84.668245 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 95.148538 iter 10 value 92.626695 iter 20 value 91.357691 iter 30 value 91.240810 iter 40 value 91.229084 iter 50 value 91.225749 iter 60 value 89.910367 iter 70 value 88.408203 iter 80 value 88.209635 iter 90 value 87.524251 iter 100 value 86.575781 final value 86.575781 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 111.683980 iter 10 value 93.357720 iter 20 value 92.727022 iter 30 value 92.706264 iter 40 value 92.696263 final value 92.695698 converged Fitting Repeat 1 # weights: 305 initial value 125.939370 iter 10 value 108.722417 iter 20 value 108.513029 iter 30 value 108.508808 final value 108.507382 converged Fitting Repeat 2 # weights: 305 initial value 141.353167 iter 10 value 117.749317 iter 20 value 109.954589 iter 30 value 108.533154 iter 40 value 108.328167 iter 50 value 108.300261 iter 60 value 105.601226 iter 70 value 104.116464 final value 103.974975 converged Fitting Repeat 3 # weights: 305 initial value 132.556699 iter 10 value 117.766817 iter 20 value 117.761480 iter 30 value 117.634458 iter 40 value 117.533640 iter 50 value 107.003584 iter 60 value 106.258491 final value 106.254441 converged Fitting Repeat 4 # weights: 305 initial value 122.809526 iter 10 value 117.894425 iter 20 value 117.875428 iter 30 value 116.671471 iter 40 value 112.137287 iter 50 value 106.532257 iter 60 value 105.922108 iter 70 value 104.959312 iter 80 value 104.911638 final value 104.910031 converged Fitting Repeat 5 # weights: 305 initial value 131.967448 iter 10 value 117.895613 iter 20 value 117.878280 iter 30 value 115.188900 iter 40 value 112.124616 iter 50 value 107.022806 iter 60 value 107.011103 iter 70 value 107.006051 iter 80 value 105.064287 iter 90 value 104.984085 iter 100 value 104.953357 final value 104.953357 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 -- Fri Oct 3 10:24:50 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 55.343 1.412 127.946
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 37.377 | 0.563 | 38.021 | |
FreqInteractors | 0.289 | 0.020 | 0.310 | |
calculateAAC | 0.045 | 0.004 | 0.050 | |
calculateAutocor | 0.689 | 0.031 | 0.724 | |
calculateCTDC | 0.095 | 0.000 | 0.095 | |
calculateCTDD | 0.747 | 0.004 | 0.751 | |
calculateCTDT | 0.264 | 0.004 | 0.268 | |
calculateCTriad | 0.467 | 0.000 | 0.468 | |
calculateDC | 0.126 | 0.004 | 0.131 | |
calculateF | 0.433 | 0.000 | 0.433 | |
calculateKSAAP | 0.140 | 0.004 | 0.144 | |
calculateQD_Sm | 2.588 | 0.020 | 2.617 | |
calculateTC | 2.321 | 0.032 | 2.356 | |
calculateTC_Sm | 0.318 | 0.000 | 0.318 | |
corr_plot | 37.056 | 0.236 | 37.335 | |
enrichfindP | 0.497 | 0.028 | 18.831 | |
enrichfind_hp | 0.080 | 0.004 | 2.147 | |
enrichplot | 0.480 | 0.008 | 0.491 | |
filter_missing_values | 0.001 | 0.000 | 0.002 | |
getFASTA | 0.076 | 0.028 | 7.741 | |
getHPI | 0.001 | 0.000 | 0.001 | |
get_negativePPI | 0.002 | 0.000 | 0.002 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0.002 | 0.000 | 0.002 | |
plotPPI | 0.089 | 0.000 | 0.089 | |
pred_ensembel | 18.648 | 0.515 | 17.991 | |
var_imp | 39.682 | 0.355 | 40.118 | |