Back to Multiple platform build/check report for BioC 3.22: simplified long |
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This page was generated on 2025-09-11 12:07 -0400 (Thu, 11 Sep 2025).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 Patched (2025-08-23 r88802) -- "Great Square Root" | 4539 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4474 |
kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-09-10 r88807) -- "Great Square Root" | 4519 |
taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4544 |
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 990/2322 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.15.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | OK | OK | ![]() | ||||||||
taishan | 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: 1.15.0 |
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_1.15.0.tar.gz |
StartedAt: 2025-09-09 07:48:46 -0000 (Tue, 09 Sep 2025) |
EndedAt: 2025-09-09 07:55:22 -0000 (Tue, 09 Sep 2025) |
EllapsedTime: 396.5 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.15.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’ * using R version 4.5.0 (2025-04-11) * 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) * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘HPiP/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘HPiP’ version ‘1.15.0’ * 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 35.806 0.391 36.544 corr_plot 34.193 0.311 34.563 FSmethod 33.440 0.599 34.094 pred_ensembel 17.995 0.630 17.435 enrichfindP 0.510 0.008 21.375 getFASTA 0.079 0.004 6.099 * 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-3.22-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-4.5.0/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.15.0’ ** 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 version 4.5.0 (2025-04-11) -- "How About a Twenty-Six" 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 98.578794 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 101.213910 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 98.324091 iter 10 value 94.047879 final value 94.026542 converged Fitting Repeat 4 # weights: 103 initial value 103.886102 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 96.870756 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 97.988649 final value 94.026542 converged Fitting Repeat 2 # weights: 305 initial value 113.354456 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 95.396342 final value 94.088889 converged Fitting Repeat 4 # weights: 305 initial value 101.097158 final value 94.026542 converged Fitting Repeat 5 # weights: 305 initial value 98.626093 final value 94.026542 converged Fitting Repeat 1 # weights: 507 initial value 100.446850 iter 10 value 91.251364 iter 20 value 88.130119 final value 88.126185 converged Fitting Repeat 2 # weights: 507 initial value 99.310173 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 100.371849 final value 94.026542 converged Fitting Repeat 4 # weights: 507 initial value 116.253715 iter 10 value 93.992035 iter 20 value 85.316494 iter 30 value 85.244058 final value 85.243423 converged Fitting Repeat 5 # weights: 507 initial value 105.697731 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 101.877837 iter 10 value 94.487124 iter 20 value 93.721292 iter 30 value 88.159736 iter 40 value 85.799636 iter 50 value 84.706371 iter 60 value 84.487688 iter 70 value 83.269836 iter 80 value 82.342552 iter 90 value 82.105392 iter 100 value 82.073313 final value 82.073313 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 102.912927 iter 10 value 94.867745 iter 20 value 94.488122 iter 30 value 94.110258 iter 40 value 86.740175 iter 50 value 86.065765 iter 60 value 84.077089 iter 70 value 83.920101 iter 80 value 83.864468 iter 90 value 83.821728 iter 100 value 83.500417 final value 83.500417 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 101.037592 iter 10 value 94.683500 iter 20 value 94.486463 iter 30 value 94.051742 iter 40 value 93.789857 iter 50 value 86.775291 iter 60 value 85.723011 iter 70 value 85.636921 iter 80 value 85.611882 iter 90 value 85.590407 iter 100 value 85.454919 final value 85.454919 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 109.697597 iter 10 value 94.439068 iter 20 value 94.077670 iter 30 value 89.396701 iter 40 value 87.689582 iter 50 value 87.359588 iter 60 value 85.899584 iter 70 value 85.410572 iter 80 value 85.284519 iter 90 value 82.558218 iter 100 value 82.348294 final value 82.348294 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 107.823078 iter 10 value 94.454502 iter 20 value 94.372604 iter 30 value 92.923640 iter 40 value 92.753721 iter 50 value 92.446309 iter 60 value 92.061097 iter 70 value 92.020187 iter 80 value 91.585612 iter 90 value 91.283115 iter 100 value 91.266433 final value 91.266433 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 113.410604 iter 10 value 94.292693 iter 20 value 89.360945 iter 30 value 87.756279 iter 40 value 85.762983 iter 50 value 85.286310 iter 60 value 85.055061 iter 70 value 84.250039 iter 80 value 82.934373 iter 90 value 82.172710 iter 100 value 81.848423 final value 81.848423 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 125.231977 iter 10 value 94.717242 iter 20 value 94.080238 iter 30 value 87.885404 iter 40 value 86.019144 iter 50 value 85.787294 iter 60 value 85.715073 iter 70 value 84.848803 iter 80 value 83.105186 iter 90 value 82.816716 iter 100 value 82.781064 final value 82.781064 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 117.470297 iter 10 value 94.013091 iter 20 value 87.722344 iter 30 value 86.162414 iter 40 value 85.516928 iter 50 value 84.889150 iter 60 value 82.951162 iter 70 value 82.093497 iter 80 value 81.151530 iter 90 value 80.869448 iter 100 value 80.708563 final value 80.708563 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 120.520719 iter 10 value 94.903085 iter 20 value 92.969201 iter 30 value 90.977662 iter 40 value 85.667359 iter 50 value 84.447708 iter 60 value 84.095891 iter 70 value 83.289787 iter 80 value 82.335715 iter 90 value 81.763042 iter 100 value 81.641931 final value 81.641931 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.712383 iter 10 value 94.508753 iter 20 value 94.192738 iter 30 value 93.812406 iter 40 value 90.225338 iter 50 value 86.866744 iter 60 value 85.509408 iter 70 value 84.434296 iter 80 value 83.806070 iter 90 value 83.293094 iter 100 value 83.230016 final value 83.230016 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 124.438649 iter 10 value 100.162471 iter 20 value 87.759378 iter 30 value 85.192271 iter 40 value 84.039414 iter 50 value 82.487643 iter 60 value 81.720906 iter 70 value 81.352745 iter 80 value 81.108449 iter 90 value 80.931677 iter 100 value 80.779038 final value 80.779038 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 109.903710 iter 10 value 94.309939 iter 20 value 92.039584 iter 30 value 85.601090 iter 40 value 82.615497 iter 50 value 82.364338 iter 60 value 81.946681 iter 70 value 80.951460 iter 80 value 80.273283 iter 90 value 80.202727 iter 100 value 80.075875 final value 80.075875 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 112.259458 iter 10 value 96.855931 iter 20 value 92.617107 iter 30 value 89.351270 iter 40 value 87.553751 iter 50 value 85.482340 iter 60 value 83.311211 iter 70 value 82.473098 iter 80 value 81.933783 iter 90 value 81.607782 iter 100 value 81.531381 final value 81.531381 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.856158 iter 10 value 95.568613 iter 20 value 92.559377 iter 30 value 86.335446 iter 40 value 85.504939 iter 50 value 83.392876 iter 60 value 81.186988 iter 70 value 80.443565 iter 80 value 80.175694 iter 90 value 80.051901 iter 100 value 79.786983 final value 79.786983 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 117.966006 iter 10 value 94.217743 iter 20 value 88.956398 iter 30 value 86.555823 iter 40 value 86.359676 iter 50 value 83.444802 iter 60 value 82.834409 iter 70 value 82.630559 iter 80 value 82.136673 iter 90 value 81.719540 iter 100 value 81.423302 final value 81.423302 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.139813 final value 94.485611 converged Fitting Repeat 2 # weights: 103 initial value 95.956162 final value 94.485877 converged Fitting Repeat 3 # weights: 103 initial value 101.373795 final value 94.485761 converged Fitting Repeat 4 # weights: 103 initial value 95.076368 final value 94.485941 converged Fitting Repeat 5 # weights: 103 initial value 95.235720 final value 94.486006 converged Fitting Repeat 1 # weights: 305 initial value 98.839696 iter 10 value 85.444838 iter 20 value 84.283009 iter 30 value 83.678560 iter 40 value 83.675597 iter 50 value 83.673588 final value 83.672626 converged Fitting Repeat 2 # weights: 305 initial value 96.230743 iter 10 value 94.031365 iter 20 value 88.965544 iter 30 value 86.897144 iter 40 value 86.618096 iter 50 value 86.617949 final value 86.617882 converged Fitting Repeat 3 # weights: 305 initial value 98.786641 iter 10 value 94.488893 iter 20 value 94.482263 iter 30 value 93.643670 iter 40 value 89.170055 iter 50 value 89.082927 iter 60 value 89.082732 iter 60 value 89.082731 iter 70 value 89.082458 iter 80 value 88.843254 iter 90 value 88.842787 iter 100 value 86.044615 final value 86.044615 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 114.554000 iter 10 value 94.107886 iter 20 value 87.162734 iter 30 value 85.914122 iter 40 value 83.743785 iter 50 value 83.552472 iter 60 value 83.549543 final value 83.549099 converged Fitting Repeat 5 # weights: 305 initial value 108.549880 iter 10 value 94.031701 iter 20 value 93.923056 iter 30 value 92.132664 iter 40 value 91.603981 iter 50 value 91.293403 iter 60 value 91.274349 iter 70 value 91.272013 iter 80 value 91.271531 final value 91.271412 converged Fitting Repeat 1 # weights: 507 initial value 104.540694 iter 10 value 94.491882 iter 20 value 94.483683 iter 30 value 94.028529 final value 94.027391 converged Fitting Repeat 2 # weights: 507 initial value 101.598151 iter 10 value 93.683434 iter 20 value 93.673457 iter 30 value 93.671182 iter 40 value 93.654330 iter 50 value 93.640002 iter 60 value 93.535804 iter 70 value 93.521259 iter 80 value 93.519010 iter 90 value 93.514452 iter 100 value 92.354896 final value 92.354896 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 102.313834 iter 10 value 94.035082 iter 20 value 93.985621 iter 30 value 93.971549 iter 40 value 89.803819 iter 50 value 86.679414 iter 60 value 86.084548 iter 70 value 86.016819 iter 80 value 86.015950 final value 86.015919 converged Fitting Repeat 4 # weights: 507 initial value 102.339345 iter 10 value 94.034467 iter 20 value 93.998864 final value 93.969842 converged Fitting Repeat 5 # weights: 507 initial value 126.521408 iter 10 value 94.485029 iter 20 value 92.138114 iter 30 value 87.991589 iter 40 value 87.698342 iter 50 value 86.075198 iter 60 value 83.695115 iter 70 value 82.217531 iter 80 value 81.987320 iter 90 value 81.904763 final value 81.904342 converged Fitting Repeat 1 # weights: 103 initial value 95.839157 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 109.401311 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 97.693776 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 109.679607 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 99.928004 iter 10 value 93.900827 final value 93.900011 converged Fitting Repeat 1 # weights: 305 initial value 98.283652 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 96.316147 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 101.411345 final value 93.869755 converged Fitting Repeat 4 # weights: 305 initial value 100.506009 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 109.311983 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 119.213151 iter 10 value 89.651443 iter 20 value 83.422980 iter 30 value 82.443130 iter 40 value 82.404533 iter 50 value 82.325798 final value 82.325732 converged Fitting Repeat 2 # weights: 507 initial value 98.141616 iter 10 value 84.012009 iter 20 value 83.964864 iter 30 value 82.100897 final value 82.021773 converged Fitting Repeat 3 # weights: 507 initial value 113.756164 final value 94.038251 converged Fitting Repeat 4 # weights: 507 initial value 98.306797 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 104.589625 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 97.262929 iter 10 value 94.056269 iter 20 value 90.826967 iter 30 value 85.971177 iter 40 value 83.545387 iter 50 value 83.383060 iter 60 value 82.815770 iter 70 value 81.567897 iter 80 value 81.527626 final value 81.527575 converged Fitting Repeat 2 # weights: 103 initial value 95.863826 iter 10 value 93.687024 iter 20 value 93.368339 iter 30 value 84.287078 iter 40 value 83.871130 iter 50 value 83.307826 iter 60 value 81.802577 iter 70 value 81.530575 iter 80 value 81.527770 iter 90 value 81.527576 final value 81.527574 converged Fitting Repeat 3 # weights: 103 initial value 102.884890 iter 10 value 94.001021 iter 20 value 90.573684 iter 30 value 87.719311 iter 40 value 83.025003 iter 50 value 81.145955 iter 60 value 81.029617 iter 70 value 80.700959 iter 80 value 80.477990 iter 90 value 80.437474 final value 80.437472 converged Fitting Repeat 4 # weights: 103 initial value 109.205123 iter 10 value 94.058371 iter 20 value 87.314210 iter 30 value 84.059212 iter 40 value 81.956217 iter 50 value 81.539356 iter 60 value 81.529201 final value 81.527575 converged Fitting Repeat 5 # weights: 103 initial value 107.124362 iter 10 value 93.992932 iter 20 value 92.717866 iter 30 value 91.388694 iter 40 value 90.913480 iter 50 value 90.030209 iter 60 value 84.122540 iter 70 value 81.996214 iter 80 value 81.592601 iter 90 value 81.528011 final value 81.527574 converged Fitting Repeat 1 # weights: 305 initial value 103.021010 iter 10 value 94.193576 iter 20 value 83.882356 iter 30 value 81.543816 iter 40 value 81.199382 iter 50 value 80.300165 iter 60 value 79.725867 iter 70 value 79.577954 iter 80 value 79.284376 iter 90 value 79.202514 iter 100 value 79.176684 final value 79.176684 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 117.894775 iter 10 value 94.043198 iter 20 value 91.961326 iter 30 value 87.134692 iter 40 value 83.452673 iter 50 value 83.138732 iter 60 value 80.709135 iter 70 value 80.330523 iter 80 value 79.947274 iter 90 value 79.824335 iter 100 value 79.317902 final value 79.317902 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 104.141608 iter 10 value 95.615436 iter 20 value 91.654218 iter 30 value 84.672488 iter 40 value 83.112555 iter 50 value 81.260220 iter 60 value 81.139362 iter 70 value 80.897785 iter 80 value 79.894808 iter 90 value 79.036803 iter 100 value 78.791038 final value 78.791038 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 110.160422 iter 10 value 93.671757 iter 20 value 90.885945 iter 30 value 85.057600 iter 40 value 82.513034 iter 50 value 80.265148 iter 60 value 79.892824 iter 70 value 79.535980 iter 80 value 79.384458 iter 90 value 79.374450 iter 100 value 79.286779 final value 79.286779 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 108.672432 iter 10 value 94.228446 iter 20 value 83.957808 iter 30 value 81.837119 iter 40 value 81.546710 iter 50 value 81.524581 iter 60 value 81.299155 iter 70 value 81.284476 iter 80 value 81.095192 iter 90 value 80.538363 iter 100 value 80.290025 final value 80.290025 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 135.416270 iter 10 value 94.431045 iter 20 value 89.211511 iter 30 value 83.781003 iter 40 value 81.849716 iter 50 value 81.590399 iter 60 value 80.793754 iter 70 value 79.767247 iter 80 value 79.569057 iter 90 value 79.370159 iter 100 value 79.308768 final value 79.308768 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 106.827668 iter 10 value 94.061955 iter 20 value 86.302416 iter 30 value 84.796948 iter 40 value 82.520703 iter 50 value 81.515329 iter 60 value 80.951757 iter 70 value 80.775329 iter 80 value 80.636264 iter 90 value 80.001142 iter 100 value 79.663169 final value 79.663169 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 111.872457 iter 10 value 93.655845 iter 20 value 84.439802 iter 30 value 82.166479 iter 40 value 81.593754 iter 50 value 81.303980 iter 60 value 81.283671 final value 81.281297 converged Fitting Repeat 4 # weights: 507 initial value 102.583823 iter 10 value 94.102722 iter 20 value 91.453659 iter 30 value 85.852548 iter 40 value 80.937460 iter 50 value 80.308956 iter 60 value 79.983082 iter 70 value 79.925869 iter 80 value 79.680886 iter 90 value 79.427298 iter 100 value 79.125773 final value 79.125773 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 106.765964 iter 10 value 98.311234 iter 20 value 90.379010 iter 30 value 85.480343 iter 40 value 82.885518 iter 50 value 81.229040 iter 60 value 81.037681 iter 70 value 81.015593 iter 80 value 80.906315 iter 90 value 79.443591 iter 100 value 79.030945 final value 79.030945 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 104.286690 final value 94.054335 converged Fitting Repeat 2 # weights: 103 initial value 100.585581 iter 10 value 94.054641 iter 20 value 94.052638 iter 30 value 94.035354 iter 40 value 93.257189 iter 50 value 93.246289 iter 60 value 84.178826 final value 82.159278 converged Fitting Repeat 3 # weights: 103 initial value 102.350074 iter 10 value 94.054746 iter 20 value 94.052230 iter 30 value 82.709977 iter 40 value 82.544368 iter 50 value 82.448405 iter 60 value 82.446874 final value 82.446626 converged Fitting Repeat 4 # weights: 103 initial value 115.455851 final value 94.054699 converged Fitting Repeat 5 # weights: 103 initial value 116.251748 iter 10 value 94.054465 iter 20 value 93.758074 iter 30 value 83.572566 iter 40 value 82.267050 iter 50 value 81.432491 iter 60 value 81.343077 iter 70 value 81.342814 iter 70 value 81.342813 iter 70 value 81.342813 final value 81.342813 converged Fitting Repeat 1 # weights: 305 initial value 101.325141 iter 10 value 94.057649 iter 20 value 92.784814 iter 30 value 82.162729 iter 40 value 82.161305 iter 50 value 81.507773 iter 60 value 80.157117 iter 70 value 80.133754 iter 80 value 79.517051 iter 90 value 78.970735 iter 100 value 78.820578 final value 78.820578 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.104786 iter 10 value 94.042943 iter 20 value 94.041912 iter 30 value 94.038515 final value 94.038489 converged Fitting Repeat 3 # weights: 305 initial value 94.386870 iter 10 value 94.056117 iter 20 value 94.041981 iter 30 value 94.041256 iter 40 value 93.880459 iter 50 value 82.185419 iter 60 value 82.163692 iter 70 value 81.972490 iter 80 value 81.923432 iter 90 value 81.729101 iter 100 value 81.725334 final value 81.725334 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 109.730148 iter 10 value 94.057777 iter 20 value 93.877774 iter 30 value 93.805535 iter 40 value 92.223667 final value 91.254286 converged Fitting Repeat 5 # weights: 305 initial value 104.457319 iter 10 value 94.058014 iter 20 value 94.053091 iter 30 value 93.552284 iter 40 value 83.861945 final value 83.535494 converged Fitting Repeat 1 # weights: 507 initial value 97.593600 iter 10 value 85.019481 iter 20 value 83.632190 iter 30 value 83.629645 iter 40 value 83.628249 iter 50 value 81.628351 iter 60 value 81.555560 iter 70 value 81.555198 iter 80 value 81.554277 final value 81.554216 converged Fitting Repeat 2 # weights: 507 initial value 96.790409 iter 10 value 93.833452 iter 20 value 93.828185 iter 30 value 93.826183 iter 30 value 93.826182 iter 30 value 93.826182 final value 93.826182 converged Fitting Repeat 3 # weights: 507 initial value 110.216077 iter 10 value 94.060854 iter 20 value 93.915841 iter 30 value 82.741497 iter 40 value 82.405205 iter 50 value 80.967420 iter 60 value 80.934963 iter 70 value 80.214992 iter 80 value 79.735194 iter 90 value 79.734661 iter 100 value 79.728396 final value 79.728396 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 97.446301 iter 10 value 94.046009 iter 20 value 94.038509 final value 94.038392 converged Fitting Repeat 5 # weights: 507 initial value 101.250249 iter 10 value 84.155119 iter 20 value 80.482623 iter 30 value 80.280891 final value 80.278633 converged Fitting Repeat 1 # weights: 103 initial value 105.700775 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 97.275174 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 106.598488 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 98.486893 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 98.439098 final value 94.050000 converged Fitting Repeat 1 # weights: 305 initial value 112.791223 iter 10 value 93.990542 final value 93.988095 converged Fitting Repeat 2 # weights: 305 initial value 105.508374 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 98.475798 iter 10 value 85.006556 iter 20 value 84.940721 iter 30 value 84.926930 iter 40 value 84.895868 iter 50 value 84.827218 iter 50 value 84.827218 iter 50 value 84.827217 final value 84.827217 converged Fitting Repeat 4 # weights: 305 initial value 95.771025 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 102.199997 final value 94.032967 converged Fitting Repeat 1 # weights: 507 initial value 108.263440 final value 94.052910 converged Fitting Repeat 2 # weights: 507 initial value 117.459741 iter 10 value 91.618225 iter 20 value 84.668264 iter 30 value 84.618295 iter 40 value 84.426597 iter 50 value 84.279948 final value 84.272860 converged Fitting Repeat 3 # weights: 507 initial value 113.732667 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 110.894733 final value 93.988095 converged Fitting Repeat 5 # weights: 507 initial value 102.532854 iter 10 value 94.045163 iter 20 value 94.032973 final value 94.032968 converged Fitting Repeat 1 # weights: 103 initial value 115.558367 iter 10 value 94.042428 iter 20 value 88.819459 iter 30 value 87.985558 iter 40 value 87.739342 iter 50 value 85.125737 iter 60 value 83.599370 iter 70 value 82.867118 iter 80 value 82.616297 iter 90 value 82.579395 final value 82.579320 converged Fitting Repeat 2 # weights: 103 initial value 106.629060 iter 10 value 94.062868 iter 20 value 94.055379 iter 30 value 89.638419 iter 40 value 84.679095 iter 50 value 84.347479 iter 60 value 84.219396 iter 70 value 83.988884 iter 80 value 82.831444 iter 90 value 82.450858 iter 100 value 82.406259 final value 82.406259 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 99.768575 iter 10 value 93.417536 iter 20 value 88.318554 iter 30 value 84.392243 iter 40 value 84.082736 iter 50 value 83.793525 iter 60 value 83.087335 iter 70 value 82.517158 iter 80 value 81.194827 iter 90 value 80.958073 final value 80.922627 converged Fitting Repeat 4 # weights: 103 initial value 101.020000 iter 10 value 93.810689 iter 20 value 88.727859 iter 30 value 86.550201 iter 40 value 86.493775 iter 50 value 83.261471 iter 60 value 82.965915 iter 70 value 82.760872 iter 80 value 81.887951 iter 90 value 81.512465 iter 100 value 81.417690 final value 81.417690 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 98.473357 iter 10 value 94.052711 iter 20 value 94.002704 iter 30 value 88.643001 iter 40 value 85.223452 iter 50 value 84.319094 iter 60 value 84.059705 iter 70 value 83.417778 iter 80 value 82.919023 iter 90 value 82.657288 iter 100 value 82.626107 final value 82.626107 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 117.407008 iter 10 value 94.102650 iter 20 value 90.634107 iter 30 value 84.523868 iter 40 value 84.171612 iter 50 value 83.677477 iter 60 value 81.397744 iter 70 value 80.986252 iter 80 value 80.042158 iter 90 value 79.883294 iter 100 value 79.694985 final value 79.694985 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 99.556275 iter 10 value 93.494615 iter 20 value 88.712798 iter 30 value 84.516557 iter 40 value 83.716845 iter 50 value 82.889027 iter 60 value 82.057151 iter 70 value 80.718682 iter 80 value 79.868880 iter 90 value 79.478541 iter 100 value 79.102866 final value 79.102866 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.369666 iter 10 value 94.136147 iter 20 value 87.910636 iter 30 value 85.138750 iter 40 value 84.917390 iter 50 value 81.962803 iter 60 value 80.074611 iter 70 value 79.639657 iter 80 value 79.320754 iter 90 value 78.955062 iter 100 value 78.754033 final value 78.754033 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 110.677705 iter 10 value 93.914254 iter 20 value 88.365872 iter 30 value 86.634220 iter 40 value 86.205418 iter 50 value 86.028938 iter 60 value 85.879950 iter 70 value 83.272600 iter 80 value 82.368535 iter 90 value 81.961563 iter 100 value 80.182310 final value 80.182310 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 101.160561 iter 10 value 94.216734 iter 20 value 94.061385 iter 30 value 93.613465 iter 40 value 85.177521 iter 50 value 83.812893 iter 60 value 81.344457 iter 70 value 79.990105 iter 80 value 79.748402 iter 90 value 79.132451 iter 100 value 78.873981 final value 78.873981 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 109.592135 iter 10 value 94.058463 iter 20 value 91.066635 iter 30 value 84.778819 iter 40 value 81.638063 iter 50 value 80.355907 iter 60 value 79.256171 iter 70 value 78.728067 iter 80 value 78.240371 iter 90 value 78.146430 iter 100 value 78.099686 final value 78.099686 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 130.840973 iter 10 value 94.877901 iter 20 value 93.270075 iter 30 value 85.436983 iter 40 value 83.845438 iter 50 value 82.815731 iter 60 value 80.762347 iter 70 value 79.416455 iter 80 value 78.812495 iter 90 value 78.614644 iter 100 value 78.441463 final value 78.441463 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.390275 iter 10 value 96.607381 iter 20 value 96.253478 iter 30 value 94.086840 iter 40 value 87.342377 iter 50 value 85.519056 iter 60 value 84.839124 iter 70 value 82.588501 iter 80 value 81.137798 iter 90 value 81.037654 iter 100 value 80.866327 final value 80.866327 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 128.365231 iter 10 value 93.753173 iter 20 value 87.847263 iter 30 value 83.558345 iter 40 value 82.304036 iter 50 value 81.074390 iter 60 value 80.463420 iter 70 value 79.934061 iter 80 value 79.406710 iter 90 value 79.201290 iter 100 value 79.142357 final value 79.142357 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 106.528152 iter 10 value 98.403229 iter 20 value 93.646048 iter 30 value 92.680354 iter 40 value 89.730212 iter 50 value 85.632389 iter 60 value 84.401291 iter 70 value 83.587481 iter 80 value 82.332411 iter 90 value 80.475043 iter 100 value 79.213879 final value 79.213879 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.989884 final value 94.054643 converged Fitting Repeat 2 # weights: 103 initial value 97.829977 final value 94.054411 converged Fitting Repeat 3 # weights: 103 initial value 103.399629 final value 94.054392 converged Fitting Repeat 4 # weights: 103 initial value 111.721191 final value 94.034619 converged Fitting Repeat 5 # weights: 103 initial value 99.101666 final value 94.054543 converged Fitting Repeat 1 # weights: 305 initial value 103.130593 iter 10 value 94.057471 iter 20 value 93.359029 iter 30 value 92.266206 iter 40 value 92.263181 iter 50 value 92.218669 iter 60 value 92.218557 iter 60 value 92.218556 iter 60 value 92.218556 final value 92.218556 converged Fitting Repeat 2 # weights: 305 initial value 100.575004 iter 10 value 94.056677 iter 20 value 94.047344 iter 30 value 84.618652 iter 40 value 83.032792 iter 50 value 82.944385 iter 60 value 82.943834 iter 70 value 82.637363 iter 80 value 82.593698 iter 90 value 82.593378 final value 82.592869 converged Fitting Repeat 3 # weights: 305 initial value 101.424841 iter 10 value 94.056006 iter 20 value 94.016584 iter 30 value 94.013310 iter 40 value 94.010749 iter 50 value 92.676690 iter 60 value 91.696427 iter 70 value 91.115854 iter 80 value 82.112907 iter 90 value 82.040106 iter 100 value 82.035612 final value 82.035612 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 109.937843 iter 10 value 94.057873 iter 20 value 94.053068 iter 30 value 84.921951 iter 40 value 84.347750 iter 50 value 82.787564 iter 60 value 79.737247 iter 70 value 79.551485 iter 80 value 78.225163 iter 90 value 78.152468 iter 100 value 78.151003 final value 78.151003 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 102.429643 iter 10 value 94.038304 iter 20 value 94.033876 iter 30 value 93.371782 iter 40 value 86.386669 iter 50 value 84.644427 iter 60 value 84.004880 iter 70 value 83.066905 iter 80 value 82.752113 iter 90 value 82.700620 iter 100 value 82.700209 final value 82.700209 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 97.645396 iter 10 value 94.041246 iter 20 value 94.038758 iter 30 value 93.895047 iter 40 value 91.251185 iter 50 value 84.533561 iter 60 value 84.430634 iter 70 value 84.429698 iter 80 value 84.428496 iter 90 value 84.428035 iter 100 value 84.426696 final value 84.426696 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 102.800672 iter 10 value 88.935641 iter 20 value 81.922833 iter 30 value 81.810937 iter 40 value 81.630638 iter 50 value 81.613840 iter 60 value 81.605759 final value 81.595693 converged Fitting Repeat 3 # weights: 507 initial value 110.325590 iter 10 value 94.041448 iter 20 value 92.035798 iter 30 value 84.919524 iter 40 value 84.840199 iter 40 value 84.840199 final value 84.840199 converged Fitting Repeat 4 # weights: 507 initial value 122.659538 iter 10 value 94.041431 iter 20 value 93.851791 iter 30 value 91.934382 iter 40 value 90.101459 iter 50 value 90.050456 iter 60 value 89.962029 iter 70 value 89.942956 iter 80 value 89.928916 iter 90 value 89.865622 iter 100 value 88.981234 final value 88.981234 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 115.338101 iter 10 value 94.060847 iter 20 value 94.036123 iter 30 value 91.823447 iter 40 value 89.089880 iter 50 value 83.441480 iter 60 value 81.282118 iter 70 value 81.069436 iter 80 value 81.023450 iter 90 value 80.982786 iter 100 value 80.925187 final value 80.925187 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.306796 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 100.897224 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 99.420457 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 109.383495 final value 94.275362 converged Fitting Repeat 5 # weights: 103 initial value 97.330564 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 108.755887 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 98.856619 iter 10 value 93.772978 final value 93.772973 converged Fitting Repeat 3 # weights: 305 initial value 104.654472 iter 10 value 91.657934 iter 20 value 91.614755 iter 30 value 91.491610 final value 91.491554 converged Fitting Repeat 4 # weights: 305 initial value 96.005168 final value 94.275362 converged Fitting Repeat 5 # weights: 305 initial value 101.730219 final value 93.456972 converged Fitting Repeat 1 # weights: 507 initial value 103.139014 iter 10 value 93.637379 iter 10 value 93.637379 iter 10 value 93.637379 final value 93.637379 converged Fitting Repeat 2 # weights: 507 initial value 113.974192 final value 94.275362 converged Fitting Repeat 3 # weights: 507 initial value 118.722315 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 97.757888 iter 10 value 94.047684 final value 93.999229 converged Fitting Repeat 5 # weights: 507 initial value 110.498918 iter 10 value 93.643864 final value 93.637379 converged Fitting Repeat 1 # weights: 103 initial value 100.083878 iter 10 value 94.467603 iter 20 value 88.573319 iter 30 value 86.415691 iter 40 value 84.561908 iter 50 value 84.292142 iter 60 value 84.286971 final value 84.286880 converged Fitting Repeat 2 # weights: 103 initial value 99.301697 iter 10 value 94.486566 iter 20 value 93.916888 iter 30 value 93.772000 iter 40 value 93.702507 iter 50 value 86.961544 iter 60 value 86.418876 iter 70 value 84.306582 iter 80 value 84.298824 iter 90 value 84.112987 iter 100 value 83.925864 final value 83.925864 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 106.519309 iter 10 value 94.574172 iter 20 value 94.446096 iter 30 value 87.779228 iter 40 value 85.655983 iter 50 value 84.453930 iter 60 value 84.325099 iter 70 value 84.300386 iter 80 value 84.286880 final value 84.286879 converged Fitting Repeat 4 # weights: 103 initial value 103.011681 iter 10 value 94.449309 iter 20 value 90.951697 iter 30 value 87.512372 iter 40 value 84.560620 iter 50 value 83.345506 iter 60 value 82.178996 iter 70 value 81.874368 iter 80 value 81.692629 iter 90 value 81.180975 final value 81.180937 converged Fitting Repeat 5 # weights: 103 initial value 96.934156 iter 10 value 88.844523 iter 20 value 85.775481 iter 30 value 84.806839 iter 40 value 84.102836 iter 50 value 83.194214 iter 60 value 83.135506 iter 70 value 81.792700 iter 80 value 81.078968 iter 90 value 80.964653 final value 80.963846 converged Fitting Repeat 1 # weights: 305 initial value 109.427474 iter 10 value 94.465730 iter 20 value 94.077836 iter 30 value 92.522019 iter 40 value 90.683052 iter 50 value 90.453743 iter 60 value 89.215186 iter 70 value 85.324288 iter 80 value 83.081061 iter 90 value 81.766661 iter 100 value 81.060676 final value 81.060676 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 100.750490 iter 10 value 94.431164 iter 20 value 93.959985 iter 30 value 88.189394 iter 40 value 85.530849 iter 50 value 84.566159 iter 60 value 83.487933 iter 70 value 83.344004 iter 80 value 83.266558 iter 90 value 81.719999 iter 100 value 80.535133 final value 80.535133 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 106.306993 iter 10 value 91.503600 iter 20 value 86.472186 iter 30 value 85.505544 iter 40 value 84.251934 iter 50 value 84.050814 iter 60 value 83.062433 iter 70 value 80.638479 iter 80 value 80.388059 iter 90 value 80.028635 iter 100 value 79.800462 final value 79.800462 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 106.499157 iter 10 value 93.569747 iter 20 value 86.935263 iter 30 value 83.602261 iter 40 value 82.994057 iter 50 value 82.896106 iter 60 value 82.463650 iter 70 value 81.773921 iter 80 value 81.176096 iter 90 value 80.901713 iter 100 value 80.310774 final value 80.310774 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 114.847601 iter 10 value 94.455805 iter 20 value 89.593654 iter 30 value 88.403021 iter 40 value 84.334598 iter 50 value 82.650204 iter 60 value 82.036215 iter 70 value 81.900487 iter 80 value 81.683478 iter 90 value 81.515502 iter 100 value 81.487586 final value 81.487586 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 120.833128 iter 10 value 91.406843 iter 20 value 85.731451 iter 30 value 83.275804 iter 40 value 82.113275 iter 50 value 82.001139 iter 60 value 81.917871 iter 70 value 81.555539 iter 80 value 81.308062 iter 90 value 80.936286 iter 100 value 79.925726 final value 79.925726 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 109.779625 iter 10 value 94.384372 iter 20 value 94.350892 iter 30 value 89.347087 iter 40 value 85.407315 iter 50 value 83.298290 iter 60 value 81.222256 iter 70 value 80.861417 iter 80 value 80.661042 iter 90 value 80.551297 iter 100 value 80.154952 final value 80.154952 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 109.805003 iter 10 value 94.602863 iter 20 value 91.455050 iter 30 value 87.345086 iter 40 value 85.844375 iter 50 value 82.525815 iter 60 value 81.251758 iter 70 value 81.118993 iter 80 value 80.925296 iter 90 value 80.843399 iter 100 value 80.316454 final value 80.316454 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 105.334240 iter 10 value 94.358526 iter 20 value 93.781515 iter 30 value 90.123051 iter 40 value 86.438502 iter 50 value 85.091578 iter 60 value 81.757562 iter 70 value 80.811055 iter 80 value 79.855456 iter 90 value 79.706083 iter 100 value 79.535818 final value 79.535818 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 109.154809 iter 10 value 94.553257 iter 20 value 90.678026 iter 30 value 84.798874 iter 40 value 84.215122 iter 50 value 82.676577 iter 60 value 82.249887 iter 70 value 81.725468 iter 80 value 81.212443 iter 90 value 80.465163 iter 100 value 80.006128 final value 80.006128 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 103.164909 final value 94.486023 converged Fitting Repeat 2 # weights: 103 initial value 97.648015 final value 94.485755 converged Fitting Repeat 3 # weights: 103 initial value 99.618302 final value 94.485846 converged Fitting Repeat 4 # weights: 103 initial value 103.025882 iter 10 value 93.639179 iter 20 value 93.638448 iter 30 value 85.304422 iter 40 value 84.039123 iter 50 value 84.000497 iter 60 value 83.678171 iter 70 value 82.855387 iter 80 value 82.579748 iter 90 value 82.153672 final value 82.088903 converged Fitting Repeat 5 # weights: 103 initial value 101.294052 final value 94.485921 converged Fitting Repeat 1 # weights: 305 initial value 102.710903 iter 10 value 94.489149 iter 20 value 88.329022 final value 85.755525 converged Fitting Repeat 2 # weights: 305 initial value 101.640361 iter 10 value 94.487763 iter 20 value 94.455968 iter 30 value 84.821522 iter 40 value 84.749713 final value 84.736403 converged Fitting Repeat 3 # weights: 305 initial value 106.994010 iter 10 value 94.489250 iter 20 value 94.408870 iter 30 value 84.076330 iter 40 value 84.055733 iter 50 value 84.052168 iter 60 value 84.039050 iter 70 value 84.038717 final value 84.037909 converged Fitting Repeat 4 # weights: 305 initial value 97.348406 iter 10 value 94.280252 iter 20 value 94.275438 iter 30 value 90.639706 iter 40 value 85.514514 iter 50 value 85.504087 iter 60 value 83.975712 iter 70 value 83.893312 iter 80 value 83.892642 final value 83.892454 converged Fitting Repeat 5 # weights: 305 initial value 102.340345 iter 10 value 94.489692 iter 20 value 94.352113 iter 30 value 91.870799 iter 40 value 91.865847 iter 50 value 91.769658 iter 60 value 91.621829 iter 70 value 86.350895 iter 80 value 83.773534 iter 90 value 83.005684 iter 100 value 82.661269 final value 82.661269 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 122.825493 iter 10 value 94.283273 iter 20 value 94.198797 iter 30 value 90.978092 iter 40 value 90.352881 iter 50 value 90.263501 iter 60 value 89.243434 iter 70 value 81.666960 iter 80 value 81.621803 iter 90 value 80.861022 iter 100 value 80.553134 final value 80.553134 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 119.035163 iter 10 value 94.492434 iter 20 value 94.281149 iter 30 value 84.182884 iter 40 value 84.068012 iter 50 value 83.958949 iter 60 value 79.934075 iter 70 value 79.057003 iter 80 value 78.867579 iter 90 value 78.656789 iter 100 value 78.603815 final value 78.603815 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 100.726683 iter 10 value 94.491100 iter 20 value 93.922757 iter 30 value 89.140817 iter 40 value 89.119628 iter 50 value 86.317290 iter 60 value 82.938650 iter 70 value 82.777078 iter 80 value 82.613641 iter 90 value 82.604289 iter 100 value 82.592913 final value 82.592913 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 112.939205 iter 10 value 90.077893 iter 20 value 87.009246 iter 30 value 87.007110 iter 40 value 86.905742 iter 50 value 83.959079 iter 60 value 81.938966 iter 70 value 81.916575 iter 80 value 81.307861 iter 90 value 81.298963 iter 100 value 81.282581 final value 81.282581 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 97.420915 iter 10 value 88.945952 iter 20 value 88.592050 iter 30 value 83.107394 iter 40 value 82.089931 iter 50 value 81.588180 iter 60 value 80.406731 iter 70 value 80.128166 iter 80 value 80.113392 iter 90 value 80.059932 iter 100 value 80.016208 final value 80.016208 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 100.193068 final value 94.275362 converged Fitting Repeat 2 # weights: 103 initial value 96.870591 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 99.973091 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 104.069955 iter 10 value 94.275363 final value 94.275362 converged Fitting Repeat 5 # weights: 103 initial value 99.553517 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 97.544072 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 101.734998 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 96.007337 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 114.517464 final value 94.105263 converged Fitting Repeat 5 # weights: 305 initial value 108.435943 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 109.580699 final value 94.275362 converged Fitting Repeat 2 # weights: 507 initial value 102.389873 iter 10 value 94.275610 final value 94.275362 converged Fitting Repeat 3 # weights: 507 initial value 107.424921 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 97.583593 final value 94.088889 converged Fitting Repeat 5 # weights: 507 initial value 109.883326 iter 10 value 93.065044 iter 20 value 92.310514 iter 30 value 92.039613 iter 40 value 91.915970 iter 50 value 91.914007 iter 60 value 90.489546 iter 70 value 90.442464 final value 90.442036 converged Fitting Repeat 1 # weights: 103 initial value 109.652318 iter 10 value 94.381065 iter 20 value 93.570247 iter 30 value 93.549090 iter 40 value 93.548698 iter 50 value 89.133801 iter 60 value 87.198392 iter 70 value 86.436845 iter 80 value 83.659860 iter 90 value 82.889751 iter 100 value 82.418746 final value 82.418746 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 105.047438 iter 10 value 94.434560 iter 20 value 90.747822 iter 30 value 89.337133 iter 40 value 89.011041 iter 50 value 84.005093 iter 60 value 82.827569 iter 70 value 82.356881 iter 80 value 82.299090 iter 90 value 82.252454 iter 100 value 82.215871 final value 82.215871 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 102.497581 iter 10 value 94.552610 iter 20 value 94.487816 iter 30 value 89.838420 iter 40 value 84.604613 iter 50 value 83.680149 iter 60 value 83.476848 iter 70 value 82.602686 iter 80 value 82.310463 iter 90 value 82.271028 iter 100 value 82.215865 final value 82.215865 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 100.844881 iter 10 value 93.509255 iter 20 value 87.410991 iter 30 value 86.073433 iter 40 value 85.725662 iter 50 value 85.452440 iter 60 value 85.300731 iter 70 value 85.221502 iter 80 value 85.151871 iter 90 value 85.134162 final value 85.134157 converged Fitting Repeat 5 # weights: 103 initial value 97.888959 iter 10 value 94.431329 iter 20 value 93.677652 iter 30 value 93.665589 iter 40 value 89.906577 iter 50 value 87.072581 iter 60 value 86.722927 iter 70 value 85.609033 iter 80 value 83.244194 iter 90 value 82.580873 iter 100 value 82.044010 final value 82.044010 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 101.589927 iter 10 value 94.214912 iter 20 value 90.973575 iter 30 value 87.736983 iter 40 value 87.112811 iter 50 value 86.253067 iter 60 value 84.253560 iter 70 value 82.540419 iter 80 value 81.598889 iter 90 value 81.250977 iter 100 value 81.220982 final value 81.220982 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 100.483481 iter 10 value 94.618400 iter 20 value 93.880082 iter 30 value 93.643573 iter 40 value 87.154821 iter 50 value 83.656586 iter 60 value 83.429248 iter 70 value 82.655007 iter 80 value 82.272647 iter 90 value 81.977909 iter 100 value 81.513356 final value 81.513356 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 99.781639 iter 10 value 94.501602 iter 20 value 93.804945 iter 30 value 91.595436 iter 40 value 90.704011 iter 50 value 84.278309 iter 60 value 83.579248 iter 70 value 83.012105 iter 80 value 82.491468 iter 90 value 82.010533 iter 100 value 81.794809 final value 81.794809 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 99.953483 iter 10 value 93.929093 iter 20 value 90.323295 iter 30 value 85.036945 iter 40 value 83.830205 iter 50 value 83.408304 iter 60 value 83.040069 iter 70 value 82.847323 iter 80 value 82.783504 iter 90 value 81.852322 iter 100 value 81.411018 final value 81.411018 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.821223 iter 10 value 94.655770 iter 20 value 87.201552 iter 30 value 84.073365 iter 40 value 82.087014 iter 50 value 81.789746 iter 60 value 81.346417 iter 70 value 81.245849 iter 80 value 81.209918 iter 90 value 81.208155 iter 100 value 81.204429 final value 81.204429 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 131.818078 iter 10 value 94.401777 iter 20 value 94.231231 iter 30 value 91.578395 iter 40 value 84.226712 iter 50 value 83.205531 iter 60 value 82.031555 iter 70 value 81.687386 iter 80 value 81.206775 iter 90 value 81.074536 iter 100 value 80.926801 final value 80.926801 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 106.325260 iter 10 value 96.603164 iter 20 value 86.475219 iter 30 value 83.412507 iter 40 value 82.620937 iter 50 value 81.986889 iter 60 value 81.433225 iter 70 value 81.304412 iter 80 value 81.138191 iter 90 value 80.952896 iter 100 value 80.799816 final value 80.799816 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 108.521880 iter 10 value 94.481521 iter 20 value 93.687388 iter 30 value 93.556128 iter 40 value 89.281291 iter 50 value 88.403712 iter 60 value 85.120075 iter 70 value 83.184257 iter 80 value 82.488262 iter 90 value 82.197298 iter 100 value 81.967532 final value 81.967532 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 108.873252 iter 10 value 94.061418 iter 20 value 89.037670 iter 30 value 87.537999 iter 40 value 87.155811 iter 50 value 84.417268 iter 60 value 83.200026 iter 70 value 82.825865 iter 80 value 82.010227 iter 90 value 81.806731 iter 100 value 81.552331 final value 81.552331 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 117.232662 iter 10 value 93.979109 iter 20 value 89.560884 iter 30 value 85.979998 iter 40 value 84.457285 iter 50 value 82.901074 iter 60 value 82.464667 iter 70 value 82.304556 iter 80 value 81.625027 iter 90 value 81.261500 iter 100 value 81.178607 final value 81.178607 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 102.018505 final value 94.486019 converged Fitting Repeat 2 # weights: 103 initial value 102.442540 final value 94.485828 converged Fitting Repeat 3 # weights: 103 initial value 95.197035 final value 94.486088 converged Fitting Repeat 4 # weights: 103 initial value 104.940293 iter 10 value 94.277099 iter 20 value 93.735108 iter 30 value 93.409714 iter 40 value 93.409480 final value 93.409478 converged Fitting Repeat 5 # weights: 103 initial value 108.470253 iter 10 value 94.787417 iter 20 value 94.707847 iter 30 value 94.488042 final value 94.484223 converged Fitting Repeat 1 # weights: 305 initial value 100.553530 iter 10 value 94.093985 iter 20 value 93.977308 iter 30 value 88.251185 iter 40 value 88.245098 iter 50 value 88.244115 iter 60 value 88.243153 iter 70 value 88.182514 iter 80 value 87.433469 iter 90 value 87.367488 final value 87.367465 converged Fitting Repeat 2 # weights: 305 initial value 98.394228 iter 10 value 94.230915 iter 20 value 91.792191 iter 30 value 91.479422 iter 40 value 91.477904 iter 50 value 91.476365 iter 60 value 91.395357 iter 70 value 91.184462 final value 91.184329 converged Fitting Repeat 3 # weights: 305 initial value 104.604090 iter 10 value 94.488901 iter 20 value 94.484235 final value 94.484214 converged Fitting Repeat 4 # weights: 305 initial value 107.326104 iter 10 value 94.489052 iter 20 value 94.313303 final value 93.559028 converged Fitting Repeat 5 # weights: 305 initial value 98.118672 iter 10 value 94.094092 iter 20 value 93.864981 iter 30 value 88.452770 iter 40 value 86.234997 iter 50 value 86.205785 iter 60 value 85.538551 iter 70 value 83.702944 iter 80 value 83.558423 iter 90 value 83.556740 iter 100 value 83.556592 final value 83.556592 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 96.291816 iter 10 value 94.492498 iter 20 value 94.460066 iter 30 value 93.426052 iter 40 value 90.025108 iter 50 value 85.549826 iter 60 value 85.460658 iter 70 value 85.265087 iter 80 value 85.191623 iter 90 value 85.186706 iter 100 value 83.629084 final value 83.629084 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 120.938210 iter 10 value 94.477053 iter 20 value 94.436270 final value 94.276578 converged Fitting Repeat 3 # weights: 507 initial value 116.104806 iter 10 value 94.097187 iter 20 value 94.089809 iter 30 value 92.933813 iter 40 value 85.422665 iter 50 value 82.976920 iter 60 value 82.712045 iter 70 value 82.691457 iter 80 value 82.664031 iter 90 value 82.650171 iter 100 value 81.604649 final value 81.604649 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 111.804476 iter 10 value 94.656049 iter 20 value 94.638029 iter 30 value 93.502875 iter 40 value 87.429745 iter 50 value 87.371449 iter 60 value 87.342274 iter 70 value 84.624862 iter 80 value 83.450154 iter 90 value 82.312349 iter 100 value 81.322510 final value 81.322510 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 98.886609 iter 10 value 94.283442 iter 20 value 94.278065 final value 94.276371 converged Fitting Repeat 1 # weights: 103 initial value 148.717623 iter 10 value 117.829206 iter 20 value 117.103485 iter 30 value 116.405972 iter 40 value 115.395378 iter 50 value 107.508180 iter 60 value 105.998922 iter 70 value 105.372116 iter 80 value 105.367589 iter 90 value 105.359732 iter 100 value 105.312941 final value 105.312941 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 126.852914 iter 10 value 116.709472 iter 20 value 112.191035 iter 30 value 111.542587 iter 40 value 110.062208 iter 50 value 107.596296 iter 60 value 107.230677 iter 70 value 106.128032 iter 80 value 105.289506 iter 90 value 105.261476 iter 100 value 105.258334 final value 105.258334 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 134.172616 iter 10 value 117.854204 iter 20 value 116.569924 iter 30 value 111.679988 iter 40 value 111.035916 iter 50 value 107.401507 iter 60 value 107.288985 iter 70 value 106.805284 iter 80 value 105.949541 iter 90 value 105.733010 iter 100 value 105.517239 final value 105.517239 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 119.940131 iter 10 value 115.927395 iter 20 value 114.135975 iter 30 value 113.877093 iter 40 value 113.818400 iter 40 value 113.818399 iter 40 value 113.818399 final value 113.818399 converged Fitting Repeat 5 # weights: 103 initial value 122.470864 iter 10 value 117.776510 iter 20 value 113.070393 iter 30 value 109.732270 iter 40 value 109.170248 iter 50 value 106.050233 iter 60 value 105.361982 iter 70 value 105.261050 iter 80 value 105.258333 iter 80 value 105.258333 iter 80 value 105.258333 final value 105.258333 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 -- Tue Sep 9 07:55:18 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 51.685 1.686 132.386
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 33.440 | 0.599 | 34.094 | |
FreqInteractors | 0.279 | 0.008 | 0.287 | |
calculateAAC | 0.044 | 0.004 | 0.048 | |
calculateAutocor | 0.636 | 0.016 | 0.655 | |
calculateCTDC | 0.089 | 0.004 | 0.093 | |
calculateCTDD | 0.744 | 0.000 | 0.746 | |
calculateCTDT | 0.243 | 0.004 | 0.248 | |
calculateCTriad | 0.428 | 0.016 | 0.445 | |
calculateDC | 0.123 | 0.000 | 0.123 | |
calculateF | 0.413 | 0.004 | 0.418 | |
calculateKSAAP | 0.135 | 0.000 | 0.136 | |
calculateQD_Sm | 2.326 | 0.020 | 2.351 | |
calculateTC | 2.257 | 0.028 | 2.290 | |
calculateTC_Sm | 0.313 | 0.008 | 0.322 | |
corr_plot | 34.193 | 0.311 | 34.563 | |
enrichfindP | 0.510 | 0.008 | 21.375 | |
enrichfind_hp | 0.079 | 0.000 | 1.383 | |
enrichplot | 0.499 | 0.000 | 0.500 | |
filter_missing_values | 0.001 | 0.000 | 0.002 | |
getFASTA | 0.079 | 0.004 | 6.099 | |
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 | 0.078 | 0.004 | 0.083 | |
pred_ensembel | 17.995 | 0.630 | 17.435 | |
var_imp | 35.806 | 0.391 | 36.544 | |