Back to Multiple platform build/check report for BioC 3.21: simplified long |
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This page was generated on 2025-08-04 11:47 -0400 (Mon, 04 Aug 2025).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 24.04.2 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4823 |
palomino7 | Windows Server 2022 Datacenter | x64 | 4.5.1 (2025-06-13 ucrt) -- "Great Square Root" | 4565 |
merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4603 |
kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4544 |
kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4579 |
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 24.04.2 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | ||||||||
merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kjohnson1 | macOS 13.6.6 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: 1.14.0 |
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: 2025-08-01 10:29:23 -0000 (Fri, 01 Aug 2025) |
EndedAt: 2025-08-01 10:35:53 -0000 (Fri, 01 Aug 2025) |
EllapsedTime: 390.3 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 38.973 0.371 39.425 corr_plot 37.421 0.371 37.862 FSmethod 37.465 0.215 37.781 pred_ensembel 17.828 0.726 17.364 enrichfindP 0.495 0.036 20.462 getFASTA 0.071 0.012 5.411 * 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 99.319323 final value 94.032967 converged Fitting Repeat 2 # weights: 103 initial value 111.569096 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 106.132402 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 98.644897 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 96.912016 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 94.316545 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 97.654267 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 100.411554 final value 94.050051 converged Fitting Repeat 4 # weights: 305 initial value 108.858350 iter 10 value 93.362090 iter 20 value 93.311194 iter 30 value 93.310694 final value 93.310690 converged Fitting Repeat 5 # weights: 305 initial value 96.780992 iter 10 value 94.053110 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 96.040957 final value 94.032967 converged Fitting Repeat 2 # weights: 507 initial value 104.549754 final value 94.052910 converged Fitting Repeat 3 # weights: 507 initial value 101.451210 iter 10 value 93.854207 final value 93.854083 converged Fitting Repeat 4 # weights: 507 initial value 97.871967 iter 10 value 92.569844 iter 20 value 92.294865 iter 30 value 92.293455 iter 30 value 92.293454 final value 92.293454 converged Fitting Repeat 5 # weights: 507 initial value 148.265349 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 102.318158 iter 10 value 94.056697 iter 20 value 90.463765 iter 30 value 87.756690 iter 40 value 87.419282 iter 50 value 86.984417 iter 60 value 86.566378 iter 70 value 85.764694 iter 80 value 85.385636 iter 90 value 85.290274 final value 85.287135 converged Fitting Repeat 2 # weights: 103 initial value 99.551098 iter 10 value 93.556650 iter 20 value 86.794545 iter 30 value 85.947387 iter 40 value 84.250313 iter 50 value 82.763694 iter 60 value 82.517112 iter 70 value 82.505680 final value 82.505254 converged Fitting Repeat 3 # weights: 103 initial value 97.510473 iter 10 value 93.916568 iter 20 value 89.161964 iter 30 value 88.016746 iter 40 value 86.910498 iter 50 value 86.021023 iter 60 value 85.400460 iter 70 value 85.304183 iter 80 value 85.287139 final value 85.287135 converged Fitting Repeat 4 # weights: 103 initial value 98.889905 iter 10 value 94.122587 iter 20 value 94.055245 iter 30 value 88.505857 iter 40 value 86.893305 iter 50 value 86.541899 iter 60 value 86.416081 iter 70 value 85.469015 iter 80 value 84.931353 iter 90 value 84.739390 iter 100 value 84.714002 final value 84.714002 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 97.070908 iter 10 value 93.942107 iter 20 value 92.705182 iter 30 value 91.322979 iter 40 value 88.498760 iter 50 value 87.213195 iter 60 value 86.669018 iter 70 value 85.832639 iter 80 value 85.343986 iter 90 value 84.908833 iter 100 value 84.717722 final value 84.717722 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 122.777644 iter 10 value 94.113286 iter 20 value 93.233879 iter 30 value 89.660195 iter 40 value 88.496822 iter 50 value 87.179620 iter 60 value 86.574771 iter 70 value 84.054625 iter 80 value 83.468580 iter 90 value 83.306046 iter 100 value 83.235987 final value 83.235987 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 100.256946 iter 10 value 94.168148 iter 20 value 88.418668 iter 30 value 87.690891 iter 40 value 85.769457 iter 50 value 84.731620 iter 60 value 82.980388 iter 70 value 81.933853 iter 80 value 81.608337 iter 90 value 81.435673 iter 100 value 81.391683 final value 81.391683 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 102.854395 iter 10 value 93.975786 iter 20 value 90.681067 iter 30 value 87.867331 iter 40 value 87.473623 iter 50 value 84.287941 iter 60 value 83.057728 iter 70 value 82.727523 iter 80 value 82.143354 iter 90 value 81.666039 iter 100 value 81.489020 final value 81.489020 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 109.331285 iter 10 value 94.097332 iter 20 value 92.599346 iter 30 value 90.330751 iter 40 value 88.253475 iter 50 value 85.872712 iter 60 value 85.729086 iter 70 value 84.591697 iter 80 value 83.413516 iter 90 value 82.367672 iter 100 value 81.858341 final value 81.858341 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 114.812878 iter 10 value 94.849052 iter 20 value 94.058345 iter 30 value 90.466336 iter 40 value 87.970357 iter 50 value 84.923944 iter 60 value 84.047432 iter 70 value 82.282878 iter 80 value 81.603553 iter 90 value 81.508878 iter 100 value 81.231496 final value 81.231496 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 108.687657 iter 10 value 95.733947 iter 20 value 92.017381 iter 30 value 87.663190 iter 40 value 86.388310 iter 50 value 84.950384 iter 60 value 82.572865 iter 70 value 82.279930 iter 80 value 82.117148 iter 90 value 81.982284 iter 100 value 81.812131 final value 81.812131 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 122.431756 iter 10 value 93.980342 iter 20 value 88.351520 iter 30 value 86.020247 iter 40 value 84.972311 iter 50 value 84.291545 iter 60 value 83.729430 iter 70 value 82.974374 iter 80 value 82.592296 iter 90 value 81.593895 iter 100 value 81.197413 final value 81.197413 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 113.621281 iter 10 value 94.052225 iter 20 value 91.057772 iter 30 value 85.507924 iter 40 value 84.660503 iter 50 value 83.130526 iter 60 value 81.954475 iter 70 value 81.392350 iter 80 value 81.158022 iter 90 value 80.998206 iter 100 value 80.925431 final value 80.925431 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 123.907148 iter 10 value 93.814498 iter 20 value 86.296532 iter 30 value 83.507496 iter 40 value 83.116228 iter 50 value 81.681077 iter 60 value 81.280373 iter 70 value 81.204023 iter 80 value 81.091429 iter 90 value 81.058368 iter 100 value 81.014850 final value 81.014850 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 104.528969 iter 10 value 94.188629 iter 20 value 93.959004 iter 30 value 88.013129 iter 40 value 86.584388 iter 50 value 86.265996 iter 60 value 85.024223 iter 70 value 84.711705 iter 80 value 84.549390 iter 90 value 84.437745 iter 100 value 84.357734 final value 84.357734 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 104.030050 final value 94.054485 converged Fitting Repeat 2 # weights: 103 initial value 95.449567 iter 10 value 94.034553 iter 20 value 94.033518 iter 30 value 93.333669 iter 40 value 92.830201 final value 92.830073 converged Fitting Repeat 3 # weights: 103 initial value 100.599045 final value 94.054636 converged Fitting Repeat 4 # weights: 103 initial value 94.808638 iter 10 value 94.020669 iter 20 value 94.018613 iter 30 value 93.036364 iter 40 value 92.825830 iter 50 value 92.824701 iter 60 value 92.823848 final value 92.823828 converged Fitting Repeat 5 # weights: 103 initial value 97.127695 final value 94.054723 converged Fitting Repeat 1 # weights: 305 initial value 105.617798 iter 10 value 94.057911 iter 20 value 94.053278 final value 94.053015 converged Fitting Repeat 2 # weights: 305 initial value 100.400993 iter 10 value 94.057548 iter 20 value 94.047519 iter 30 value 93.031093 iter 40 value 89.384311 iter 50 value 85.536496 iter 60 value 85.171470 iter 70 value 84.471558 iter 80 value 83.889938 iter 90 value 83.658581 iter 100 value 83.653470 final value 83.653470 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 94.946688 iter 10 value 94.056219 final value 94.052923 converged Fitting Repeat 4 # weights: 305 initial value 96.334759 iter 10 value 94.057855 iter 20 value 94.044257 iter 30 value 88.999014 iter 40 value 87.365617 iter 50 value 87.361800 iter 60 value 87.360763 iter 70 value 87.276801 iter 80 value 87.136808 iter 90 value 83.610417 iter 100 value 83.088362 final value 83.088362 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 102.358654 iter 10 value 94.057487 iter 20 value 94.054425 iter 30 value 94.035495 final value 94.034235 converged Fitting Repeat 1 # weights: 507 initial value 111.908088 iter 10 value 94.061533 iter 20 value 94.051122 iter 30 value 93.931643 iter 40 value 93.081892 iter 50 value 92.687081 iter 60 value 92.686068 iter 70 value 88.323134 iter 80 value 86.932648 iter 90 value 86.912052 iter 100 value 86.265829 final value 86.265829 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 97.688634 iter 10 value 94.024637 iter 20 value 94.018504 iter 30 value 93.206977 iter 40 value 92.901039 iter 50 value 92.797261 final value 92.797204 converged Fitting Repeat 3 # weights: 507 initial value 107.031896 iter 10 value 93.952078 iter 20 value 93.949126 iter 30 value 93.883315 iter 40 value 93.882933 iter 50 value 93.809395 iter 60 value 87.751745 iter 70 value 87.086474 iter 80 value 85.930306 iter 90 value 83.760185 iter 100 value 83.755022 final value 83.755022 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 121.060076 iter 10 value 94.041220 iter 20 value 94.035258 iter 30 value 94.022074 iter 40 value 88.606851 iter 50 value 88.155162 iter 60 value 88.145855 final value 88.144961 converged Fitting Repeat 5 # weights: 507 initial value 98.218285 iter 10 value 94.061449 iter 20 value 93.947047 iter 30 value 92.843853 iter 40 value 92.841556 final value 92.841422 converged Fitting Repeat 1 # weights: 103 initial value 103.030848 final value 93.860355 converged Fitting Repeat 2 # weights: 103 initial value 97.065659 final value 93.836066 converged Fitting Repeat 3 # weights: 103 initial value 94.378072 final value 93.836066 converged Fitting Repeat 4 # weights: 103 initial value 95.633005 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 98.456681 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 100.932029 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 97.168458 final value 93.900000 converged Fitting Repeat 3 # weights: 305 initial value 96.306745 iter 10 value 93.720460 iter 20 value 93.017565 final value 92.701657 converged Fitting Repeat 4 # weights: 305 initial value 107.936111 final value 93.836066 converged Fitting Repeat 5 # weights: 305 initial value 122.253270 iter 10 value 93.862892 final value 93.860355 converged Fitting Repeat 1 # weights: 507 initial value 106.507448 final value 94.052910 converged Fitting Repeat 2 # weights: 507 initial value 97.558352 final value 94.011429 converged Fitting Repeat 3 # weights: 507 initial value 95.873417 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 103.244816 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 97.291142 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 102.521092 iter 10 value 94.054867 iter 20 value 90.377740 iter 30 value 89.454751 iter 40 value 88.150599 iter 50 value 87.401259 iter 60 value 86.919695 iter 70 value 86.654358 final value 86.651613 converged Fitting Repeat 2 # weights: 103 initial value 111.395861 iter 10 value 94.060605 iter 20 value 94.056720 iter 30 value 93.867081 iter 40 value 93.803380 iter 50 value 93.697975 iter 60 value 89.340631 iter 70 value 88.654053 iter 80 value 88.384058 iter 90 value 88.263103 iter 100 value 88.099207 final value 88.099207 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 103.149916 iter 10 value 94.055063 iter 20 value 94.010019 iter 30 value 93.049444 iter 40 value 92.948965 iter 50 value 88.197577 iter 60 value 87.432261 iter 70 value 86.656690 iter 80 value 85.935308 iter 90 value 85.903659 iter 100 value 85.878019 final value 85.878019 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 101.879117 iter 10 value 93.976463 iter 20 value 89.825404 iter 30 value 89.073381 iter 40 value 88.776371 iter 50 value 88.374716 iter 60 value 86.223611 iter 70 value 85.767401 iter 80 value 85.751283 iter 90 value 85.726381 iter 100 value 85.722339 final value 85.722339 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 96.234648 iter 10 value 94.057872 iter 20 value 93.959522 iter 30 value 89.295625 iter 40 value 87.837486 iter 50 value 87.448247 iter 60 value 87.281192 iter 70 value 87.221477 iter 80 value 87.194273 iter 80 value 87.194273 iter 80 value 87.194273 final value 87.194273 converged Fitting Repeat 1 # weights: 305 initial value 105.948823 iter 10 value 94.210878 iter 20 value 93.700462 iter 30 value 88.636374 iter 40 value 87.952513 iter 50 value 86.189915 iter 60 value 85.297018 iter 70 value 84.784922 iter 80 value 84.640347 iter 90 value 84.534541 iter 100 value 84.447233 final value 84.447233 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 104.699851 iter 10 value 94.783901 iter 20 value 94.588557 iter 30 value 88.901579 iter 40 value 88.623246 iter 50 value 87.617234 iter 60 value 87.233019 iter 70 value 87.151472 iter 80 value 87.116142 iter 90 value 87.029035 iter 100 value 86.561483 final value 86.561483 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 111.935065 iter 10 value 93.891263 iter 20 value 90.596534 iter 30 value 89.417433 iter 40 value 88.739178 iter 50 value 88.653862 iter 60 value 88.525864 iter 70 value 88.484647 iter 80 value 86.832387 iter 90 value 85.383640 iter 100 value 84.761867 final value 84.761867 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 121.131010 iter 10 value 93.771713 iter 20 value 90.122515 iter 30 value 89.403115 iter 40 value 88.792470 iter 50 value 87.807855 iter 60 value 86.748310 iter 70 value 86.707002 iter 80 value 86.025373 iter 90 value 85.476090 iter 100 value 84.872595 final value 84.872595 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 112.886892 iter 10 value 94.009250 iter 20 value 90.908462 iter 30 value 88.891045 iter 40 value 87.701267 iter 50 value 86.294812 iter 60 value 85.789810 iter 70 value 85.697116 iter 80 value 85.675533 iter 90 value 85.662041 final value 85.661792 converged Fitting Repeat 1 # weights: 507 initial value 112.590496 iter 10 value 94.095605 iter 20 value 89.246483 iter 30 value 88.665276 iter 40 value 86.120196 iter 50 value 85.206856 iter 60 value 84.877520 iter 70 value 84.640568 iter 80 value 84.510740 iter 90 value 84.298840 iter 100 value 84.161592 final value 84.161592 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 113.051306 iter 10 value 94.617311 iter 20 value 94.052377 iter 30 value 88.927045 iter 40 value 88.594567 iter 50 value 88.006824 iter 60 value 87.507788 iter 70 value 87.239336 iter 80 value 86.957147 iter 90 value 86.635284 iter 100 value 86.496879 final value 86.496879 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 106.068842 iter 10 value 94.242715 iter 20 value 93.812736 iter 30 value 90.312704 iter 40 value 88.240875 iter 50 value 86.386710 iter 60 value 85.330722 iter 70 value 84.743716 iter 80 value 84.506415 iter 90 value 84.464214 iter 100 value 84.337558 final value 84.337558 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 138.500146 iter 10 value 93.928026 iter 20 value 92.737845 iter 30 value 91.016974 iter 40 value 88.872878 iter 50 value 86.612596 iter 60 value 86.104415 iter 70 value 85.440298 iter 80 value 85.203164 iter 90 value 85.090873 iter 100 value 84.714575 final value 84.714575 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 105.896280 iter 10 value 94.057915 iter 20 value 93.741832 iter 30 value 92.665129 iter 40 value 89.368354 iter 50 value 87.570602 iter 60 value 86.746000 iter 70 value 85.475030 iter 80 value 85.139885 iter 90 value 84.951281 iter 100 value 84.770018 final value 84.770018 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.883294 final value 94.054522 converged Fitting Repeat 2 # weights: 103 initial value 102.034971 final value 94.054465 converged Fitting Repeat 3 # weights: 103 initial value 95.536195 final value 93.837556 converged Fitting Repeat 4 # weights: 103 initial value 100.899445 final value 94.054590 converged Fitting Repeat 5 # weights: 103 initial value 111.305711 iter 10 value 93.837986 iter 20 value 93.817583 iter 30 value 93.704797 iter 40 value 89.707726 iter 50 value 88.889522 final value 88.872725 converged Fitting Repeat 1 # weights: 305 initial value 95.335338 iter 10 value 94.057416 iter 20 value 94.052998 iter 30 value 92.113322 iter 40 value 89.825213 iter 50 value 88.593751 iter 60 value 88.546060 iter 70 value 87.374501 final value 87.370384 converged Fitting Repeat 2 # weights: 305 initial value 105.498934 iter 10 value 94.057823 iter 20 value 93.934863 iter 30 value 88.595749 iter 40 value 88.170882 iter 50 value 88.169229 iter 60 value 88.132909 iter 70 value 87.751935 final value 87.750518 converged Fitting Repeat 3 # weights: 305 initial value 106.622523 iter 10 value 94.057531 iter 20 value 93.572057 iter 30 value 88.536567 iter 40 value 88.535697 iter 50 value 88.399570 iter 60 value 88.118154 iter 70 value 88.118041 iter 70 value 88.118041 final value 88.118041 converged Fitting Repeat 4 # weights: 305 initial value 96.836561 iter 10 value 93.769986 iter 20 value 93.706533 iter 30 value 90.162731 iter 40 value 90.159899 iter 50 value 89.720639 iter 60 value 89.458767 iter 70 value 87.987061 iter 80 value 86.620672 iter 90 value 84.620030 iter 100 value 83.747794 final value 83.747794 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 96.333454 iter 10 value 94.057299 iter 20 value 94.052919 iter 30 value 94.007108 iter 40 value 93.760977 iter 50 value 93.721092 iter 60 value 87.698203 iter 70 value 87.027333 iter 80 value 86.262354 iter 90 value 84.518239 iter 100 value 84.140718 final value 84.140718 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 100.145863 iter 10 value 94.060830 iter 20 value 93.226126 iter 30 value 88.598871 iter 40 value 88.593362 final value 88.593346 converged Fitting Repeat 2 # weights: 507 initial value 98.936507 iter 10 value 93.768759 iter 20 value 93.764507 iter 30 value 93.745583 iter 40 value 93.687387 final value 93.687239 converged Fitting Repeat 3 # weights: 507 initial value 101.116658 iter 10 value 94.059503 iter 20 value 94.037156 iter 30 value 94.035451 iter 40 value 94.030945 iter 50 value 94.028452 iter 60 value 93.880128 iter 70 value 89.029656 iter 80 value 86.811440 iter 90 value 86.810914 iter 100 value 86.517292 final value 86.517292 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 105.212521 iter 10 value 93.881016 iter 20 value 93.433587 iter 30 value 93.388414 iter 40 value 92.075728 iter 50 value 91.996595 iter 60 value 91.916177 iter 70 value 91.909165 iter 80 value 88.765362 iter 90 value 88.154856 iter 100 value 87.653466 final value 87.653466 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 97.928854 iter 10 value 93.791315 iter 20 value 93.741000 iter 30 value 93.735719 iter 40 value 93.733159 final value 93.730028 converged Fitting Repeat 1 # weights: 103 initial value 103.193889 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 95.708551 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 102.175855 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 99.537390 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 97.235753 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 104.843955 final value 94.466823 converged Fitting Repeat 2 # weights: 305 initial value 104.393831 final value 93.688363 converged Fitting Repeat 3 # weights: 305 initial value 115.221215 iter 10 value 94.466823 iter 10 value 94.466823 iter 10 value 94.466823 final value 94.466823 converged Fitting Repeat 4 # weights: 305 initial value 99.961422 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 102.701745 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 95.153096 final value 94.466823 converged Fitting Repeat 2 # weights: 507 initial value 96.361419 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 94.968509 final value 94.466823 converged Fitting Repeat 4 # weights: 507 initial value 104.977698 final value 94.466823 converged Fitting Repeat 5 # weights: 507 initial value 119.932816 iter 10 value 86.219587 iter 20 value 80.700776 iter 30 value 80.686475 iter 40 value 80.686362 final value 80.686354 converged Fitting Repeat 1 # weights: 103 initial value 102.723439 iter 10 value 94.486941 iter 20 value 85.333418 iter 30 value 76.682548 iter 40 value 76.175619 iter 50 value 76.024184 iter 60 value 75.772285 iter 70 value 75.339050 iter 80 value 75.163236 final value 75.162008 converged Fitting Repeat 2 # weights: 103 initial value 104.840839 iter 10 value 94.442844 iter 20 value 90.859421 iter 30 value 87.751849 iter 40 value 84.765513 iter 50 value 84.186242 iter 60 value 83.366216 iter 70 value 83.337537 iter 80 value 81.485062 iter 90 value 81.434469 iter 100 value 81.037644 final value 81.037644 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 100.462580 iter 10 value 94.466757 iter 20 value 88.914566 iter 30 value 81.377656 iter 40 value 80.631804 iter 50 value 78.805147 iter 60 value 75.460569 iter 70 value 75.316876 iter 80 value 75.175939 iter 90 value 75.162280 final value 75.162008 converged Fitting Repeat 4 # weights: 103 initial value 104.376323 iter 10 value 93.781481 iter 20 value 87.757166 iter 30 value 86.129271 iter 40 value 80.756837 iter 50 value 80.145520 iter 60 value 79.260323 iter 70 value 78.954338 iter 80 value 78.633615 iter 90 value 78.625216 final value 78.625206 converged Fitting Repeat 5 # weights: 103 initial value 98.753960 iter 10 value 94.049664 iter 20 value 77.724362 iter 30 value 77.470793 iter 40 value 76.990350 iter 50 value 76.205328 iter 60 value 75.297222 iter 70 value 75.262590 iter 80 value 75.217975 final value 75.217895 converged Fitting Repeat 1 # weights: 305 initial value 103.308740 iter 10 value 92.310245 iter 20 value 82.146577 iter 30 value 81.494895 iter 40 value 78.944899 iter 50 value 76.373120 iter 60 value 75.455991 iter 70 value 74.795306 iter 80 value 74.345011 iter 90 value 74.298245 iter 100 value 74.243440 final value 74.243440 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 101.142964 iter 10 value 92.101934 iter 20 value 80.335559 iter 30 value 79.403004 iter 40 value 78.435633 iter 50 value 76.443269 iter 60 value 75.832678 iter 70 value 75.021814 iter 80 value 73.920757 iter 90 value 73.687327 iter 100 value 73.550620 final value 73.550620 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 111.582304 iter 10 value 98.057905 iter 20 value 95.744982 iter 30 value 90.870110 iter 40 value 81.620642 iter 50 value 78.894210 iter 60 value 78.284155 iter 70 value 77.173442 iter 80 value 77.035322 iter 90 value 76.652046 iter 100 value 75.520261 final value 75.520261 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 111.684176 iter 10 value 91.575467 iter 20 value 87.859957 iter 30 value 87.272104 iter 40 value 85.902832 iter 50 value 80.796863 iter 60 value 77.242014 iter 70 value 76.818919 iter 80 value 76.734112 iter 90 value 76.325683 iter 100 value 76.219498 final value 76.219498 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 109.544794 iter 10 value 94.478853 iter 20 value 86.576587 iter 30 value 78.073171 iter 40 value 76.627603 iter 50 value 75.132969 iter 60 value 74.601858 iter 70 value 74.076703 iter 80 value 73.694716 iter 90 value 73.626857 iter 100 value 73.590056 final value 73.590056 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 116.493303 iter 10 value 94.604418 iter 20 value 84.232588 iter 30 value 80.762851 iter 40 value 80.326688 iter 50 value 76.545737 iter 60 value 75.130715 iter 70 value 74.475971 iter 80 value 74.244421 iter 90 value 74.211785 iter 100 value 73.980695 final value 73.980695 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 122.122441 iter 10 value 97.254748 iter 20 value 90.461674 iter 30 value 85.269561 iter 40 value 83.519500 iter 50 value 80.590458 iter 60 value 77.058698 iter 70 value 76.487562 iter 80 value 76.195318 iter 90 value 76.133680 iter 100 value 76.079312 final value 76.079312 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 129.060500 iter 10 value 94.614427 iter 20 value 82.588018 iter 30 value 80.946077 iter 40 value 77.960718 iter 50 value 75.168549 iter 60 value 74.092726 iter 70 value 73.855248 iter 80 value 73.801668 iter 90 value 73.780759 iter 100 value 73.725176 final value 73.725176 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 123.470133 iter 10 value 94.755922 iter 20 value 94.331512 iter 30 value 83.201741 iter 40 value 81.268199 iter 50 value 77.488909 iter 60 value 76.638945 iter 70 value 75.179099 iter 80 value 74.526250 iter 90 value 74.371655 iter 100 value 74.346189 final value 74.346189 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 108.695723 iter 10 value 92.926436 iter 20 value 86.369451 iter 30 value 78.193300 iter 40 value 77.406319 iter 50 value 77.166930 iter 60 value 76.574292 iter 70 value 75.440586 iter 80 value 75.057187 iter 90 value 74.917918 iter 100 value 74.632423 final value 74.632423 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.000504 final value 94.485774 converged Fitting Repeat 2 # weights: 103 initial value 99.312180 final value 94.485491 converged Fitting Repeat 3 # weights: 103 initial value 97.364229 iter 10 value 91.464148 iter 20 value 91.422822 iter 30 value 91.417202 iter 40 value 89.328956 iter 50 value 87.498261 iter 60 value 86.595417 iter 70 value 86.524288 final value 86.518213 converged Fitting Repeat 4 # weights: 103 initial value 95.399102 final value 94.485866 converged Fitting Repeat 5 # weights: 103 initial value 96.910645 final value 94.485942 converged Fitting Repeat 1 # weights: 305 initial value 103.373360 iter 10 value 94.489233 iter 20 value 94.483943 iter 30 value 91.658776 iter 40 value 91.652519 final value 91.652253 converged Fitting Repeat 2 # weights: 305 initial value 105.842979 iter 10 value 93.693787 iter 20 value 93.691002 iter 30 value 93.646654 iter 40 value 93.646383 iter 40 value 93.646383 iter 40 value 93.646383 final value 93.646383 converged Fitting Repeat 3 # weights: 305 initial value 96.381786 iter 10 value 91.239480 iter 20 value 82.805924 iter 30 value 82.666792 iter 40 value 82.665657 iter 50 value 82.664758 iter 60 value 77.562848 iter 70 value 74.747384 iter 80 value 73.712873 iter 90 value 72.827292 iter 100 value 72.593731 final value 72.593731 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 98.031864 iter 10 value 93.933079 iter 20 value 81.689104 iter 30 value 76.262489 iter 40 value 76.235271 iter 50 value 76.231851 iter 60 value 75.851374 iter 70 value 75.672108 iter 80 value 75.570325 iter 90 value 75.568365 iter 100 value 75.567400 final value 75.567400 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 95.733559 iter 10 value 83.205459 iter 20 value 82.180506 iter 30 value 82.172710 final value 82.170109 converged Fitting Repeat 1 # weights: 507 initial value 119.014829 iter 10 value 85.889614 iter 20 value 83.935564 iter 30 value 83.238590 iter 40 value 83.234414 iter 50 value 83.231966 iter 60 value 78.782977 iter 70 value 74.659180 iter 80 value 74.641066 iter 90 value 74.638628 final value 74.638036 converged Fitting Repeat 2 # weights: 507 initial value 95.756663 iter 10 value 94.260905 iter 20 value 94.231146 final value 94.230066 converged Fitting Repeat 3 # weights: 507 initial value 99.424472 iter 10 value 93.286574 iter 20 value 91.656210 iter 30 value 91.650828 iter 40 value 91.615080 iter 50 value 91.495206 iter 60 value 91.490563 final value 91.490549 converged Fitting Repeat 4 # weights: 507 initial value 101.956615 iter 10 value 94.491270 iter 20 value 91.608363 iter 30 value 91.591511 iter 40 value 91.188260 iter 50 value 86.784584 iter 60 value 83.162750 iter 70 value 80.482267 iter 80 value 79.447602 final value 79.436858 converged Fitting Repeat 5 # weights: 507 initial value 98.619152 iter 10 value 94.365816 iter 20 value 92.636413 iter 30 value 82.582768 iter 40 value 78.691676 iter 50 value 78.691134 final value 78.689735 converged Fitting Repeat 1 # weights: 103 initial value 95.956503 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 109.047754 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 109.891585 final value 94.484210 converged Fitting Repeat 4 # weights: 103 initial value 94.843142 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 100.208995 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 100.774771 iter 10 value 94.428841 final value 94.428839 converged Fitting Repeat 2 # weights: 305 initial value 113.937455 iter 10 value 94.396674 iter 20 value 87.576344 iter 30 value 84.855271 iter 40 value 84.783393 final value 84.783333 converged Fitting Repeat 3 # weights: 305 initial value 109.633830 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 98.010678 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 103.711985 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 96.631210 iter 10 value 93.772984 final value 93.772973 converged Fitting Repeat 2 # weights: 507 initial value 110.073290 final value 94.030602 converged Fitting Repeat 3 # weights: 507 initial value 98.490875 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 108.637057 iter 10 value 86.915617 iter 20 value 81.860709 final value 81.582895 converged Fitting Repeat 5 # weights: 507 initial value 95.480979 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 112.813282 iter 10 value 93.854766 iter 20 value 87.223102 iter 30 value 86.745735 iter 40 value 86.435297 iter 50 value 84.344736 iter 60 value 81.956071 iter 70 value 81.912962 iter 80 value 80.479050 iter 90 value 79.280767 iter 100 value 78.433810 final value 78.433810 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 97.834464 iter 10 value 94.495294 iter 20 value 94.485461 iter 30 value 89.258746 iter 40 value 83.073176 iter 50 value 81.569038 iter 60 value 81.125192 iter 70 value 80.868629 iter 80 value 80.701237 iter 90 value 80.652360 iter 100 value 80.647480 final value 80.647480 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 97.970429 iter 10 value 94.068332 iter 20 value 89.061181 iter 30 value 80.777710 iter 40 value 79.322960 iter 50 value 78.912509 iter 60 value 78.546545 iter 70 value 78.483461 final value 78.482942 converged Fitting Repeat 4 # weights: 103 initial value 106.722395 iter 10 value 94.380067 iter 20 value 82.917350 iter 30 value 80.216601 iter 40 value 79.955389 iter 50 value 79.650050 iter 60 value 78.368074 iter 70 value 78.267635 iter 80 value 78.267386 iter 80 value 78.267386 final value 78.267386 converged Fitting Repeat 5 # weights: 103 initial value 98.059399 iter 10 value 94.658033 iter 20 value 94.483076 iter 30 value 82.140992 iter 40 value 81.853233 iter 50 value 80.107039 iter 60 value 80.098358 final value 80.098347 converged Fitting Repeat 1 # weights: 305 initial value 124.949979 iter 10 value 94.436757 iter 20 value 91.845824 iter 30 value 83.596440 iter 40 value 82.336948 iter 50 value 81.542652 iter 60 value 81.218005 iter 70 value 79.059380 iter 80 value 77.827179 iter 90 value 76.834877 iter 100 value 76.691723 final value 76.691723 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 106.168103 iter 10 value 94.489196 iter 20 value 85.591667 iter 30 value 82.487888 iter 40 value 79.994006 iter 50 value 78.992833 iter 60 value 78.049063 iter 70 value 77.609445 iter 80 value 76.619236 iter 90 value 76.367761 iter 100 value 76.308836 final value 76.308836 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 119.469494 iter 10 value 94.469084 iter 20 value 89.206080 iter 30 value 82.152513 iter 40 value 81.040851 iter 50 value 79.789120 iter 60 value 78.407064 iter 70 value 76.970921 iter 80 value 76.788817 iter 90 value 76.662001 iter 100 value 76.453018 final value 76.453018 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 102.196113 iter 10 value 94.045268 iter 20 value 83.172870 iter 30 value 81.924155 iter 40 value 79.981792 iter 50 value 79.533100 iter 60 value 78.352478 iter 70 value 77.915130 iter 80 value 77.848547 iter 90 value 77.730476 iter 100 value 77.143041 final value 77.143041 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 104.816677 iter 10 value 94.682885 iter 20 value 93.830685 iter 30 value 88.653002 iter 40 value 86.677339 iter 50 value 83.162807 iter 60 value 79.127265 iter 70 value 78.453429 iter 80 value 78.244864 iter 90 value 77.179336 iter 100 value 76.597221 final value 76.597221 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 103.819203 iter 10 value 94.092423 iter 20 value 81.223888 iter 30 value 80.835625 iter 40 value 80.483451 iter 50 value 79.728083 iter 60 value 77.876333 iter 70 value 77.834423 iter 80 value 77.499055 iter 90 value 77.131942 iter 100 value 76.569361 final value 76.569361 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 104.372041 iter 10 value 91.412363 iter 20 value 89.366970 iter 30 value 82.192607 iter 40 value 81.119455 iter 50 value 80.878708 iter 60 value 78.736097 iter 70 value 77.162928 iter 80 value 76.959370 iter 90 value 76.828298 iter 100 value 76.799341 final value 76.799341 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 102.317169 iter 10 value 95.254928 iter 20 value 85.826584 iter 30 value 79.828460 iter 40 value 78.988413 iter 50 value 78.458720 iter 60 value 78.170768 iter 70 value 78.086057 iter 80 value 77.881248 iter 90 value 77.580824 iter 100 value 76.751953 final value 76.751953 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 104.792146 iter 10 value 94.276150 iter 20 value 85.375304 iter 30 value 82.895644 iter 40 value 82.549429 iter 50 value 79.898465 iter 60 value 79.404843 iter 70 value 78.758880 iter 80 value 77.379540 iter 90 value 76.882760 iter 100 value 76.657375 final value 76.657375 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 115.168259 iter 10 value 94.955378 iter 20 value 93.973150 iter 30 value 87.203478 iter 40 value 86.290386 iter 50 value 85.832804 iter 60 value 81.839121 iter 70 value 78.867675 iter 80 value 77.971334 iter 90 value 77.611868 iter 100 value 77.134164 final value 77.134164 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 103.055328 final value 94.485916 converged Fitting Repeat 2 # weights: 103 initial value 96.507686 final value 94.485798 converged Fitting Repeat 3 # weights: 103 initial value 106.388652 iter 10 value 93.775099 iter 20 value 93.773818 iter 30 value 93.493621 final value 93.453729 converged Fitting Repeat 4 # weights: 103 initial value 96.664854 final value 94.485888 converged Fitting Repeat 5 # weights: 103 initial value 97.794038 final value 94.486022 converged Fitting Repeat 1 # weights: 305 initial value 131.568322 iter 10 value 94.489574 iter 20 value 94.200649 iter 30 value 80.753545 iter 40 value 79.934980 iter 50 value 79.205785 iter 60 value 78.995384 iter 70 value 78.964961 iter 80 value 78.960410 iter 90 value 78.878598 iter 100 value 78.756272 final value 78.756272 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 96.971223 iter 10 value 93.779147 iter 20 value 93.777529 iter 30 value 93.775528 iter 40 value 93.775356 iter 50 value 93.565551 iter 60 value 84.246247 final value 84.231320 converged Fitting Repeat 3 # weights: 305 initial value 98.210625 iter 10 value 93.778912 iter 20 value 93.778208 iter 30 value 93.471858 iter 40 value 93.456122 iter 50 value 93.416626 iter 60 value 90.035880 iter 70 value 88.405263 iter 80 value 88.304133 iter 90 value 88.303953 final value 88.303593 converged Fitting Repeat 4 # weights: 305 initial value 101.533816 iter 10 value 94.488877 iter 20 value 94.180676 iter 30 value 82.225465 iter 40 value 81.992770 iter 50 value 79.919707 iter 60 value 78.815723 iter 70 value 78.812117 iter 80 value 78.467395 iter 90 value 78.205755 iter 100 value 78.121112 final value 78.121112 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 96.955359 iter 10 value 94.488788 iter 20 value 94.473106 iter 30 value 93.637949 iter 30 value 93.637948 iter 30 value 93.637948 final value 93.637948 converged Fitting Repeat 1 # weights: 507 initial value 95.093711 iter 10 value 93.308586 iter 20 value 85.637556 iter 30 value 80.827215 iter 40 value 79.507349 iter 50 value 78.201709 iter 60 value 77.598294 iter 70 value 77.447916 iter 80 value 77.141374 final value 77.140666 converged Fitting Repeat 2 # weights: 507 initial value 98.405637 iter 10 value 93.781374 iter 20 value 93.572967 iter 30 value 85.209206 iter 40 value 82.487575 iter 50 value 82.076834 iter 60 value 82.071668 iter 70 value 82.071216 iter 80 value 82.041636 iter 90 value 81.859409 iter 100 value 81.857507 final value 81.857507 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 132.718120 iter 10 value 94.492709 iter 20 value 93.997119 iter 30 value 90.655123 iter 40 value 90.654457 iter 40 value 90.654456 iter 40 value 90.654456 final value 90.654456 converged Fitting Repeat 4 # weights: 507 initial value 138.737429 iter 10 value 94.492666 iter 20 value 94.484077 iter 30 value 89.092968 iter 40 value 81.317632 iter 50 value 80.867485 iter 60 value 78.767307 iter 70 value 78.749011 final value 78.748802 converged Fitting Repeat 5 # weights: 507 initial value 109.795185 iter 10 value 93.781773 iter 20 value 93.744518 iter 30 value 81.041348 final value 81.010418 converged Fitting Repeat 1 # weights: 103 initial value 96.474622 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 98.794441 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 96.760337 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 118.136120 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 97.067902 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 124.229426 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 94.745488 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 105.701573 final value 94.466823 converged Fitting Repeat 4 # weights: 305 initial value 99.980919 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 112.932692 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 96.081172 final value 94.312038 converged Fitting Repeat 2 # weights: 507 initial value 101.196254 final value 94.466823 converged Fitting Repeat 3 # weights: 507 initial value 107.304034 final value 94.466823 converged Fitting Repeat 4 # weights: 507 initial value 117.255773 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 128.483252 final value 94.466823 converged Fitting Repeat 1 # weights: 103 initial value 107.226839 iter 10 value 94.422556 iter 20 value 88.820170 iter 30 value 86.232487 iter 40 value 84.808274 iter 50 value 83.947881 iter 60 value 83.656757 iter 70 value 83.313640 iter 80 value 83.094995 iter 90 value 82.837426 iter 100 value 82.664720 final value 82.664720 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 103.165894 iter 10 value 94.490161 iter 20 value 93.835790 iter 30 value 92.368803 iter 40 value 92.162355 iter 50 value 92.094860 iter 60 value 91.997551 iter 70 value 85.442652 iter 80 value 84.736940 iter 90 value 84.013763 iter 100 value 83.094181 final value 83.094181 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 106.860512 iter 10 value 93.921728 iter 20 value 91.725000 iter 30 value 90.710152 iter 40 value 86.739260 iter 50 value 84.743409 iter 60 value 83.191769 iter 70 value 82.881030 iter 80 value 82.669795 iter 90 value 82.665763 iter 90 value 82.665762 iter 90 value 82.665762 final value 82.665762 converged Fitting Repeat 4 # weights: 103 initial value 99.547106 iter 10 value 94.498899 iter 20 value 94.485318 iter 30 value 94.342419 iter 40 value 92.943557 iter 50 value 90.089808 iter 60 value 87.025995 iter 70 value 86.098722 iter 80 value 86.016268 iter 90 value 85.557910 iter 100 value 84.865392 final value 84.865392 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 106.730373 iter 10 value 94.488281 iter 20 value 94.486707 iter 30 value 93.488747 iter 40 value 88.329679 iter 50 value 87.118644 iter 60 value 85.550669 iter 70 value 85.454146 final value 85.453975 converged Fitting Repeat 1 # weights: 305 initial value 110.538105 iter 10 value 94.729227 iter 20 value 90.889462 iter 30 value 86.771199 iter 40 value 86.477547 iter 50 value 85.374016 iter 60 value 82.784392 iter 70 value 82.190069 iter 80 value 81.814914 iter 90 value 81.661133 iter 100 value 81.417911 final value 81.417911 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.277046 iter 10 value 94.508307 iter 20 value 93.391946 iter 30 value 92.019487 iter 40 value 91.248930 iter 50 value 85.729249 iter 60 value 84.095974 iter 70 value 82.607234 iter 80 value 82.184915 iter 90 value 81.633050 iter 100 value 81.522547 final value 81.522547 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 101.478386 iter 10 value 94.643629 iter 20 value 90.717849 iter 30 value 88.870825 iter 40 value 88.055607 iter 50 value 86.267859 iter 60 value 83.080702 iter 70 value 82.125036 iter 80 value 81.906229 iter 90 value 81.711063 iter 100 value 81.341906 final value 81.341906 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 101.580674 iter 10 value 94.306902 iter 20 value 90.202006 iter 30 value 88.052558 iter 40 value 85.809692 iter 50 value 84.739458 iter 60 value 83.787191 iter 70 value 83.377951 iter 80 value 83.109100 iter 90 value 81.716395 iter 100 value 81.488612 final value 81.488612 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 108.605196 iter 10 value 93.949003 iter 20 value 92.503215 iter 30 value 92.073344 iter 40 value 91.987751 iter 50 value 91.823491 iter 60 value 89.996130 iter 70 value 84.108764 iter 80 value 83.135443 iter 90 value 82.237531 iter 100 value 82.057540 final value 82.057540 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 109.842605 iter 10 value 94.522097 iter 20 value 89.222361 iter 30 value 87.082978 iter 40 value 85.377494 iter 50 value 84.610643 iter 60 value 83.473861 iter 70 value 82.703688 iter 80 value 82.142645 iter 90 value 82.055205 iter 100 value 81.956250 final value 81.956250 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 117.307909 iter 10 value 95.112199 iter 20 value 93.503848 iter 30 value 92.565366 iter 40 value 89.138126 iter 50 value 86.858624 iter 60 value 84.884703 iter 70 value 84.443549 iter 80 value 83.296545 iter 90 value 82.410436 iter 100 value 82.151674 final value 82.151674 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 118.653817 iter 10 value 94.392121 iter 20 value 93.100892 iter 30 value 90.043660 iter 40 value 86.779712 iter 50 value 83.192051 iter 60 value 82.221630 iter 70 value 81.558538 iter 80 value 81.252374 iter 90 value 81.104944 iter 100 value 81.010341 final value 81.010341 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 136.560632 iter 10 value 94.533678 iter 20 value 93.872096 iter 30 value 92.946089 iter 40 value 91.210919 iter 50 value 88.077405 iter 60 value 85.405151 iter 70 value 84.400587 iter 80 value 84.128856 iter 90 value 83.092388 iter 100 value 82.252002 final value 82.252002 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 105.372801 iter 10 value 94.635035 iter 20 value 93.307736 iter 30 value 87.189169 iter 40 value 85.893806 iter 50 value 85.428544 iter 60 value 85.038464 iter 70 value 83.414265 iter 80 value 82.214458 iter 90 value 81.419997 iter 100 value 81.267411 final value 81.267411 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.230747 final value 94.485592 converged Fitting Repeat 2 # weights: 103 initial value 94.600658 final value 94.485859 converged Fitting Repeat 3 # weights: 103 initial value 98.940107 final value 94.485814 converged Fitting Repeat 4 # weights: 103 initial value 99.134665 iter 10 value 94.485509 final value 94.484704 converged Fitting Repeat 5 # weights: 103 initial value 96.202109 iter 10 value 94.485736 final value 94.484434 converged Fitting Repeat 1 # weights: 305 initial value 114.372647 iter 10 value 94.488927 iter 20 value 94.484239 iter 30 value 93.874273 iter 40 value 88.264191 iter 50 value 88.144255 iter 60 value 88.141822 iter 70 value 86.186016 iter 80 value 85.997195 iter 90 value 84.621225 iter 100 value 82.456336 final value 82.456336 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 103.888625 iter 10 value 92.573092 iter 20 value 92.473448 iter 30 value 92.414041 iter 40 value 92.047043 iter 50 value 92.035282 final value 92.032663 converged Fitting Repeat 3 # weights: 305 initial value 97.924490 iter 10 value 94.488737 iter 20 value 94.296879 iter 30 value 86.186661 iter 40 value 85.891867 iter 50 value 85.253263 iter 60 value 84.823025 iter 70 value 84.375532 iter 80 value 81.472133 iter 90 value 81.146695 iter 100 value 81.114189 final value 81.114189 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 101.129611 iter 10 value 94.489245 iter 20 value 94.442320 iter 30 value 94.317231 iter 40 value 94.315306 iter 50 value 94.312705 iter 60 value 94.311753 final value 94.311661 converged Fitting Repeat 5 # weights: 305 initial value 118.726808 iter 10 value 94.489321 iter 20 value 94.484239 iter 30 value 94.421647 iter 40 value 88.579610 final value 88.556653 converged Fitting Repeat 1 # weights: 507 initial value 113.426884 iter 10 value 94.475129 iter 20 value 94.261678 iter 30 value 94.259560 iter 40 value 94.253769 iter 50 value 94.252270 final value 94.252224 converged Fitting Repeat 2 # weights: 507 initial value 118.417522 iter 10 value 94.492432 iter 20 value 94.466826 iter 30 value 88.509595 iter 40 value 84.163740 iter 50 value 83.941665 iter 60 value 83.877511 iter 70 value 83.865825 iter 80 value 82.585425 iter 90 value 82.495866 iter 100 value 82.464185 final value 82.464185 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 96.032578 iter 10 value 94.492184 iter 20 value 94.467445 iter 30 value 94.467136 final value 94.467110 converged Fitting Repeat 4 # weights: 507 initial value 99.026425 iter 10 value 94.475329 iter 20 value 94.467351 final value 94.467074 converged Fitting Repeat 5 # weights: 507 initial value 100.133915 iter 10 value 94.494509 iter 20 value 94.481681 iter 30 value 92.813019 iter 40 value 85.876015 iter 50 value 83.469302 final value 83.273517 converged Fitting Repeat 1 # weights: 305 initial value 140.005833 iter 10 value 117.895154 iter 20 value 117.843520 final value 117.758783 converged Fitting Repeat 2 # weights: 305 initial value 120.498792 iter 10 value 117.895055 iter 20 value 117.890310 iter 30 value 117.026106 iter 40 value 109.122634 iter 50 value 108.417063 iter 60 value 107.070492 iter 70 value 107.050854 iter 80 value 106.883710 iter 90 value 105.587004 iter 100 value 105.252303 final value 105.252303 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 126.632469 iter 10 value 117.895484 iter 20 value 117.890447 final value 117.890424 converged Fitting Repeat 4 # weights: 305 initial value 124.271699 iter 10 value 110.924787 iter 20 value 110.083162 iter 30 value 110.037847 iter 40 value 110.036248 iter 50 value 108.772364 iter 60 value 108.150917 iter 70 value 108.129762 iter 80 value 108.127852 final value 108.126649 converged Fitting Repeat 5 # weights: 305 initial value 178.156941 iter 10 value 117.916144 iter 20 value 117.909466 iter 30 value 112.405353 iter 40 value 106.806311 iter 50 value 106.664071 iter 60 value 106.661524 iter 70 value 106.459494 iter 80 value 106.433386 iter 90 value 106.430416 final value 106.423358 converged svmRadial ranger Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases RUNIT TEST PROTOCOL -- Fri Aug 1 10:35:49 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 52.753 1.288 117.456
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 37.465 | 0.215 | 37.781 | |
FreqInteractors | 0.285 | 0.024 | 0.316 | |
calculateAAC | 0.049 | 0.000 | 0.049 | |
calculateAutocor | 0.692 | 0.028 | 0.723 | |
calculateCTDC | 0.093 | 0.004 | 0.098 | |
calculateCTDD | 0.827 | 0.000 | 0.830 | |
calculateCTDT | 0.268 | 0.004 | 0.273 | |
calculateCTriad | 0.476 | 0.004 | 0.481 | |
calculateDC | 0.132 | 0.000 | 0.132 | |
calculateF | 0.457 | 0.000 | 0.459 | |
calculateKSAAP | 0.141 | 0.004 | 0.145 | |
calculateQD_Sm | 2.308 | 0.012 | 2.325 | |
calculateTC | 2.450 | 0.040 | 2.494 | |
calculateTC_Sm | 0.332 | 0.000 | 0.334 | |
corr_plot | 37.421 | 0.371 | 37.862 | |
enrichfindP | 0.495 | 0.036 | 20.462 | |
enrichfind_hp | 0.083 | 0.004 | 1.397 | |
enrichplot | 0.546 | 0.092 | 0.639 | |
filter_missing_values | 0.001 | 0.000 | 0.002 | |
getFASTA | 0.071 | 0.012 | 5.411 | |
getHPI | 0.001 | 0.000 | 0.000 | |
get_negativePPI | 0.000 | 0.003 | 0.002 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0.001 | 0.000 | 0.002 | |
plotPPI | 0.087 | 0.004 | 0.092 | |
pred_ensembel | 17.828 | 0.726 | 17.364 | |
var_imp | 38.973 | 0.371 | 39.425 | |