Back to Multiple platform build/check report for BioC 3.22: simplified long |
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This page was generated on 2025-08-09 12:08 -0400 (Sat, 09 Aug 2025).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4818 |
palomino8 | Windows Server 2022 Datacenter | x64 | 4.5.1 (2025-06-13 ucrt) -- "Great Square Root" | 4553 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4595 |
kjohnson3 | macOS 13.7.1 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4537 |
Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X |
Package 987/2317 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.15.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.2 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | ||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kjohnson3 | macOS 13.7.1 Ventura / arm64 | OK | OK | OK | OK | ![]() | ||||||||
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
Package: HPiP |
Version: 1.15.0 |
Command: /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.15.0.tar.gz |
StartedAt: 2025-08-08 21:39:22 -0400 (Fri, 08 Aug 2025) |
EndedAt: 2025-08-08 21:45:42 -0400 (Fri, 08 Aug 2025) |
EllapsedTime: 380.2 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD check --install=check:HPiP.install-out.txt --library=/Library/Frameworks/R.framework/Resources/library --no-vignettes --timings HPiP_1.15.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’ * using R version 4.5.1 (2025-06-13) * using platform: x86_64-apple-darwin20 * R was compiled by Apple clang version 14.0.0 (clang-1400.0.29.202) GNU Fortran (GCC) 14.2.0 * running under: macOS Monterey 12.7.6 * 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 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 35.827 2.083 38.507 corr_plot 33.665 1.875 35.919 FSmethod 33.582 1.839 35.764 pred_ensembel 13.964 0.451 12.456 enrichfindP 0.467 0.057 8.220 * 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 ‘/Users/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck/00check.log’ for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /Library/Frameworks/R.framework/Resources/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/Library/Frameworks/R.framework/Versions/4.5-x86_64/Resources/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 4.5.1 (2025-06-13) -- "Great Square Root" Copyright (C) 2025 The R Foundation for Statistical Computing Platform: x86_64-apple-darwin20 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > BiocGenerics:::testPackage('HPiP') No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE avNNet Loading required package: ggplot2 Loading required package: lattice Fitting Repeat 1 # weights: 103 initial value 99.904149 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 97.542288 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 99.161190 iter 10 value 93.836066 iter 10 value 93.836066 iter 10 value 93.836066 final value 93.836066 converged Fitting Repeat 4 # weights: 103 initial value 111.335446 iter 10 value 94.043243 iter 10 value 94.043243 iter 10 value 94.043243 final value 94.043243 converged Fitting Repeat 5 # weights: 103 initial value 100.098513 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 102.384403 iter 10 value 94.043246 final value 94.043243 converged Fitting Repeat 2 # weights: 305 initial value 132.646726 iter 10 value 94.052910 iter 10 value 94.052910 iter 10 value 94.052910 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 101.366558 final value 94.017143 converged Fitting Repeat 4 # weights: 305 initial value 96.285579 final value 94.043243 converged Fitting Repeat 5 # weights: 305 initial value 100.463978 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 104.461515 iter 10 value 92.361775 iter 20 value 91.588269 final value 91.587993 converged Fitting Repeat 2 # weights: 507 initial value 117.547288 final value 94.043243 converged Fitting Repeat 3 # weights: 507 initial value 97.501674 final value 94.052910 converged Fitting Repeat 4 # weights: 507 initial value 95.583521 final value 92.190657 converged Fitting Repeat 5 # weights: 507 initial value 100.812637 final value 94.043243 converged Fitting Repeat 1 # weights: 103 initial value 102.616116 iter 10 value 94.007032 iter 20 value 92.256826 iter 30 value 85.928791 iter 40 value 84.516525 iter 50 value 82.491723 iter 60 value 80.269222 iter 70 value 79.622687 iter 80 value 78.898798 iter 90 value 78.714374 final value 78.711494 converged Fitting Repeat 2 # weights: 103 initial value 95.998283 iter 10 value 93.916121 iter 20 value 83.011107 iter 30 value 81.645118 iter 40 value 81.278562 iter 50 value 80.188346 iter 60 value 80.051459 final value 80.051018 converged Fitting Repeat 3 # weights: 103 initial value 103.394110 iter 10 value 94.057369 iter 20 value 85.614831 iter 30 value 82.467420 iter 40 value 82.359096 iter 50 value 81.446336 iter 60 value 80.293943 iter 70 value 79.742242 iter 80 value 79.633280 final value 79.632894 converged Fitting Repeat 4 # weights: 103 initial value 105.069943 iter 10 value 94.050910 iter 20 value 92.109562 iter 30 value 87.672792 iter 40 value 81.739555 iter 50 value 80.723345 iter 60 value 80.191441 iter 70 value 80.052375 final value 80.051018 converged Fitting Repeat 5 # weights: 103 initial value 97.608036 iter 10 value 94.038886 iter 20 value 89.121864 iter 30 value 85.982263 iter 40 value 84.061623 iter 50 value 83.618005 iter 60 value 83.204125 iter 70 value 83.029860 iter 80 value 81.764919 iter 90 value 80.501762 iter 100 value 79.818215 final value 79.818215 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 104.078116 iter 10 value 95.285200 iter 20 value 83.651977 iter 30 value 82.030922 iter 40 value 81.143474 iter 50 value 80.558749 iter 60 value 78.709941 iter 70 value 78.677356 iter 80 value 78.672189 iter 90 value 78.600715 iter 100 value 78.260576 final value 78.260576 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 99.670240 iter 10 value 93.980860 iter 20 value 88.033103 iter 30 value 82.275950 iter 40 value 79.757986 iter 50 value 78.984231 iter 60 value 77.940620 iter 70 value 77.611726 iter 80 value 77.325717 iter 90 value 77.091763 iter 100 value 77.014654 final value 77.014654 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 106.359270 iter 10 value 93.804846 iter 20 value 91.800192 iter 30 value 86.021437 iter 40 value 83.923670 iter 50 value 80.963941 iter 60 value 79.529208 iter 70 value 79.237267 iter 80 value 78.873496 iter 90 value 78.798769 iter 100 value 78.552425 final value 78.552425 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.637426 iter 10 value 94.020474 iter 20 value 91.884702 iter 30 value 91.296043 iter 40 value 88.994288 iter 50 value 80.473761 iter 60 value 78.144499 iter 70 value 77.442087 iter 80 value 77.188612 iter 90 value 77.075280 iter 100 value 77.057418 final value 77.057418 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 108.861526 iter 10 value 94.060418 iter 20 value 93.148815 iter 30 value 83.880382 iter 40 value 81.621666 iter 50 value 81.187776 iter 60 value 80.783891 iter 70 value 80.401530 iter 80 value 79.817186 iter 90 value 79.628904 iter 100 value 79.563808 final value 79.563808 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 110.261763 iter 10 value 93.998964 iter 20 value 89.309306 iter 30 value 82.615541 iter 40 value 80.118714 iter 50 value 79.475342 iter 60 value 78.380330 iter 70 value 77.991387 iter 80 value 77.808389 iter 90 value 77.371551 iter 100 value 77.061786 final value 77.061786 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 122.091116 iter 10 value 95.365197 iter 20 value 94.086946 iter 30 value 94.049320 iter 40 value 87.803836 iter 50 value 84.615103 iter 60 value 83.902929 iter 70 value 83.226721 iter 80 value 82.920607 iter 90 value 82.513488 iter 100 value 79.989079 final value 79.989079 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 114.915169 iter 10 value 91.903719 iter 20 value 86.406124 iter 30 value 79.458951 iter 40 value 78.181025 iter 50 value 77.688033 iter 60 value 77.592751 iter 70 value 77.363003 iter 80 value 77.294620 iter 90 value 77.136475 iter 100 value 77.040014 final value 77.040014 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 113.788497 iter 10 value 94.091231 iter 20 value 92.139522 iter 30 value 87.601999 iter 40 value 80.885139 iter 50 value 78.997793 iter 60 value 78.293867 iter 70 value 77.748844 iter 80 value 77.439043 iter 90 value 77.212114 iter 100 value 77.103267 final value 77.103267 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 107.682961 iter 10 value 93.974080 iter 20 value 89.450256 iter 30 value 86.956585 iter 40 value 83.284743 iter 50 value 81.868089 iter 60 value 78.902227 iter 70 value 78.045513 iter 80 value 77.428736 iter 90 value 77.190446 iter 100 value 77.046524 final value 77.046524 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 104.418783 final value 94.054631 converged Fitting Repeat 2 # weights: 103 initial value 96.868838 final value 94.054545 converged Fitting Repeat 3 # weights: 103 initial value 100.180395 final value 94.054634 converged Fitting Repeat 4 # weights: 103 initial value 101.163596 iter 10 value 94.054365 iter 20 value 94.052935 final value 94.052914 converged Fitting Repeat 5 # weights: 103 initial value 112.916424 final value 94.054584 converged Fitting Repeat 1 # weights: 305 initial value 95.059954 iter 10 value 94.048335 iter 20 value 93.845622 iter 30 value 85.391492 iter 40 value 81.920917 iter 50 value 81.920276 final value 81.920275 converged Fitting Repeat 2 # weights: 305 initial value 97.937261 iter 10 value 94.057631 iter 20 value 94.052917 iter 30 value 82.394026 iter 40 value 81.688453 iter 50 value 81.676563 iter 60 value 81.663760 final value 81.663455 converged Fitting Repeat 3 # weights: 305 initial value 102.922780 iter 10 value 94.047895 iter 20 value 94.043351 iter 30 value 94.043194 iter 40 value 91.167133 iter 50 value 90.786081 iter 60 value 90.785367 iter 70 value 90.785046 iter 80 value 90.715064 iter 90 value 90.604300 iter 100 value 90.386901 final value 90.386901 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 110.337826 iter 10 value 93.959634 iter 20 value 93.907787 iter 30 value 81.091908 iter 40 value 80.944020 final value 80.943797 converged Fitting Repeat 5 # weights: 305 initial value 107.570089 iter 10 value 93.950159 iter 20 value 85.699870 iter 30 value 82.558191 iter 40 value 81.962447 iter 50 value 81.899008 iter 60 value 81.830717 iter 70 value 81.761636 iter 80 value 80.968394 iter 90 value 80.962591 iter 100 value 80.950714 final value 80.950714 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 100.924006 iter 10 value 94.060956 iter 20 value 94.054284 iter 30 value 94.051116 iter 40 value 93.998161 iter 50 value 91.753569 iter 60 value 84.003420 iter 70 value 83.277375 iter 80 value 82.705321 iter 90 value 82.612949 iter 100 value 82.553855 final value 82.553855 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 95.706714 iter 10 value 94.061753 iter 20 value 94.032028 iter 30 value 93.062706 iter 40 value 85.245351 iter 50 value 83.457978 iter 60 value 81.423141 iter 70 value 81.244312 iter 80 value 81.239340 iter 90 value 81.238320 iter 100 value 78.933717 final value 78.933717 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 101.375106 iter 10 value 94.036091 iter 20 value 93.794463 iter 30 value 93.537489 iter 40 value 93.534588 iter 50 value 93.510788 iter 60 value 91.060485 iter 70 value 82.771092 iter 80 value 82.729273 iter 90 value 82.214869 iter 100 value 82.124882 final value 82.124882 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 101.900940 iter 10 value 94.060824 iter 20 value 93.310964 iter 30 value 82.879893 iter 40 value 82.877647 iter 50 value 82.875660 iter 60 value 82.601388 iter 70 value 82.569208 iter 80 value 82.352415 iter 90 value 78.946265 iter 100 value 77.773217 final value 77.773217 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 101.041464 iter 10 value 91.794166 iter 20 value 89.422678 iter 30 value 89.402325 iter 40 value 89.364668 iter 50 value 89.359027 iter 60 value 79.846569 iter 70 value 77.801311 iter 80 value 77.646926 iter 90 value 77.605239 iter 100 value 77.472449 final value 77.472449 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.405930 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 95.677216 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 104.899119 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 101.421269 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 118.214961 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 98.206920 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 132.236198 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 104.512813 iter 10 value 94.026542 iter 10 value 94.026542 iter 10 value 94.026542 final value 94.026542 converged Fitting Repeat 4 # weights: 305 initial value 99.318177 final value 94.026542 converged Fitting Repeat 5 # weights: 305 initial value 133.505966 iter 10 value 94.026543 iter 10 value 94.026542 iter 10 value 94.026542 final value 94.026542 converged Fitting Repeat 1 # weights: 507 initial value 123.094926 final value 94.433545 converged Fitting Repeat 2 # weights: 507 initial value 101.369333 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 96.876046 iter 10 value 90.485770 iter 20 value 89.843543 iter 30 value 89.705319 iter 40 value 89.679107 final value 89.678936 converged Fitting Repeat 4 # weights: 507 initial value 97.905001 iter 10 value 92.077084 iter 20 value 91.199058 iter 30 value 91.198092 final value 91.198086 converged Fitting Repeat 5 # weights: 507 initial value 120.058493 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 103.729580 iter 10 value 94.497044 iter 20 value 94.167275 iter 30 value 94.130642 iter 40 value 94.025295 iter 50 value 93.757197 iter 60 value 93.695470 iter 70 value 87.996176 iter 80 value 86.140883 iter 90 value 85.810494 iter 100 value 83.900294 final value 83.900294 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 102.754603 iter 10 value 94.358726 iter 20 value 86.700707 iter 30 value 86.398561 iter 40 value 85.004855 iter 50 value 83.861079 iter 60 value 83.559019 iter 70 value 83.247444 iter 80 value 83.109578 iter 90 value 83.038101 iter 100 value 83.027998 final value 83.027998 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 98.961810 iter 10 value 92.463475 iter 20 value 87.505011 iter 30 value 85.767704 iter 40 value 85.359141 iter 50 value 83.932818 iter 60 value 83.651156 iter 70 value 83.239596 final value 83.211874 converged Fitting Repeat 4 # weights: 103 initial value 101.935074 iter 10 value 94.486616 iter 20 value 93.976082 iter 30 value 93.751892 iter 40 value 93.749549 iter 50 value 93.682145 iter 60 value 93.671261 iter 70 value 90.556895 iter 80 value 85.009262 iter 90 value 84.863187 iter 100 value 84.787123 final value 84.787123 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 108.138879 iter 10 value 94.979532 iter 20 value 94.490132 iter 30 value 93.803717 iter 40 value 93.307678 iter 50 value 90.049956 iter 60 value 85.826592 iter 70 value 85.031235 iter 80 value 84.167620 iter 90 value 84.069718 iter 100 value 83.916557 final value 83.916557 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 112.398130 iter 10 value 94.469832 iter 20 value 93.731724 iter 30 value 93.194481 iter 40 value 86.036518 iter 50 value 84.386388 iter 60 value 84.053777 iter 70 value 83.281932 iter 80 value 82.196179 iter 90 value 81.829114 iter 100 value 81.780229 final value 81.780229 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 118.847992 iter 10 value 94.415479 iter 20 value 93.821884 iter 30 value 93.736508 iter 40 value 93.453630 iter 50 value 92.050891 iter 60 value 86.361211 iter 70 value 85.043194 iter 80 value 84.012679 iter 90 value 82.999493 iter 100 value 82.691520 final value 82.691520 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 107.852727 iter 10 value 94.285941 iter 20 value 93.565625 iter 30 value 90.131465 iter 40 value 87.487790 iter 50 value 85.073939 iter 60 value 84.469515 iter 70 value 83.404038 iter 80 value 83.158174 iter 90 value 82.760487 iter 100 value 82.505931 final value 82.505931 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 101.376670 iter 10 value 94.308885 iter 20 value 93.737839 iter 30 value 93.562538 iter 40 value 87.337827 iter 50 value 86.117914 iter 60 value 84.410604 iter 70 value 82.538633 iter 80 value 82.005013 iter 90 value 81.807193 iter 100 value 81.642583 final value 81.642583 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.255382 iter 10 value 93.869551 iter 20 value 93.740934 iter 30 value 93.012969 iter 40 value 85.512288 iter 50 value 84.626777 iter 60 value 83.954499 iter 70 value 83.590078 iter 80 value 82.791516 iter 90 value 82.297738 iter 100 value 82.181770 final value 82.181770 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 132.814651 iter 10 value 95.603806 iter 20 value 91.620749 iter 30 value 86.426571 iter 40 value 84.986136 iter 50 value 84.611631 iter 60 value 84.432321 iter 70 value 84.165117 iter 80 value 83.962936 iter 90 value 83.670896 iter 100 value 82.879625 final value 82.879625 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 106.215348 iter 10 value 94.494678 iter 20 value 94.273298 iter 30 value 86.266234 iter 40 value 85.889653 iter 50 value 85.392440 iter 60 value 84.094176 iter 70 value 82.975413 iter 80 value 82.777263 iter 90 value 82.615229 iter 100 value 82.552773 final value 82.552773 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 107.652461 iter 10 value 92.338817 iter 20 value 91.110087 iter 30 value 87.799902 iter 40 value 86.516429 iter 50 value 85.627747 iter 60 value 84.708163 iter 70 value 84.093857 iter 80 value 83.901927 iter 90 value 83.828029 iter 100 value 83.442093 final value 83.442093 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 106.729244 iter 10 value 94.567365 iter 20 value 89.529126 iter 30 value 87.963506 iter 40 value 87.538731 iter 50 value 87.176798 iter 60 value 86.863623 iter 70 value 84.812880 iter 80 value 83.939793 iter 90 value 82.853657 iter 100 value 82.236271 final value 82.236271 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 129.575836 iter 10 value 94.066515 iter 20 value 88.276205 iter 30 value 86.341886 iter 40 value 85.603661 iter 50 value 85.203319 iter 60 value 84.685639 iter 70 value 83.968451 iter 80 value 83.709264 iter 90 value 83.107354 iter 100 value 82.764809 final value 82.764809 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 117.323732 iter 10 value 94.630392 iter 20 value 94.603650 iter 30 value 94.486266 final value 94.484218 converged Fitting Repeat 2 # weights: 103 initial value 95.371540 iter 10 value 94.485853 iter 20 value 94.342535 iter 30 value 88.743238 iter 40 value 88.411995 iter 50 value 88.398686 iter 60 value 88.384755 iter 70 value 87.894307 iter 80 value 87.177340 final value 87.177338 converged Fitting Repeat 3 # weights: 103 initial value 99.031958 final value 94.485623 converged Fitting Repeat 4 # weights: 103 initial value 96.219365 final value 94.485747 converged Fitting Repeat 5 # weights: 103 initial value 95.746315 iter 10 value 94.485843 iter 20 value 94.484250 final value 94.484215 converged Fitting Repeat 1 # weights: 305 initial value 122.977665 iter 10 value 94.491016 iter 20 value 94.484701 final value 94.484302 converged Fitting Repeat 2 # weights: 305 initial value 114.251345 iter 10 value 94.489151 iter 20 value 94.428361 iter 30 value 87.947284 iter 40 value 85.599149 iter 50 value 85.382965 iter 60 value 85.380334 iter 70 value 85.378656 final value 85.378279 converged Fitting Repeat 3 # weights: 305 initial value 104.186569 iter 10 value 88.473058 iter 20 value 87.226534 final value 87.224080 converged Fitting Repeat 4 # weights: 305 initial value 111.687456 iter 10 value 94.489214 iter 20 value 94.484230 iter 30 value 94.321999 iter 40 value 93.640905 final value 93.640903 converged Fitting Repeat 5 # weights: 305 initial value 109.150099 iter 10 value 94.488761 iter 20 value 92.061783 iter 30 value 92.031655 iter 40 value 91.508033 iter 50 value 88.403847 iter 60 value 87.457751 final value 87.382609 converged Fitting Repeat 1 # weights: 507 initial value 106.938263 iter 10 value 94.154102 iter 20 value 94.152211 iter 30 value 94.145678 iter 40 value 94.102876 iter 50 value 93.555538 iter 60 value 93.488419 iter 70 value 93.486004 iter 80 value 93.482635 iter 90 value 93.473159 iter 100 value 93.390857 final value 93.390857 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 101.953719 iter 10 value 91.911095 iter 20 value 85.399858 iter 30 value 85.182708 iter 40 value 84.179320 iter 50 value 84.175895 iter 60 value 83.692278 iter 70 value 83.651158 iter 80 value 83.211695 iter 90 value 82.441134 iter 100 value 82.316579 final value 82.316579 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 103.504476 iter 10 value 93.600240 iter 20 value 93.584872 iter 30 value 93.579488 iter 40 value 93.213934 iter 50 value 92.321424 iter 60 value 92.320323 iter 70 value 92.311132 final value 92.310991 converged Fitting Repeat 4 # weights: 507 initial value 114.958915 iter 10 value 94.034920 iter 20 value 94.028302 final value 94.027683 converged Fitting Repeat 5 # weights: 507 initial value 111.462360 iter 10 value 87.342527 iter 20 value 86.605852 iter 30 value 86.596233 iter 40 value 86.537975 iter 50 value 86.533559 iter 60 value 86.476171 iter 70 value 86.277187 iter 80 value 85.310319 iter 90 value 84.790793 iter 100 value 84.669022 final value 84.669022 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 101.221774 final value 93.915746 converged Fitting Repeat 2 # weights: 103 initial value 102.211509 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 101.380911 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 96.140707 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 98.575627 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 94.232397 iter 10 value 93.016715 iter 20 value 87.142115 iter 30 value 86.100958 iter 40 value 86.099607 final value 86.099605 converged Fitting Repeat 2 # weights: 305 initial value 111.839905 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 95.353585 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 94.376544 iter 10 value 85.557144 iter 20 value 83.931899 iter 30 value 83.584722 iter 40 value 83.575960 iter 40 value 83.575960 final value 83.575960 converged Fitting Repeat 5 # weights: 305 initial value 98.734935 iter 10 value 93.724711 iter 10 value 93.724711 iter 10 value 93.724711 final value 93.724711 converged Fitting Repeat 1 # weights: 507 initial value 109.337192 iter 10 value 94.179692 final value 93.946237 converged Fitting Repeat 2 # weights: 507 initial value 97.536762 final value 94.008696 converged Fitting Repeat 3 # weights: 507 initial value 101.841260 iter 10 value 93.491549 iter 20 value 92.824798 iter 30 value 92.815736 final value 92.815715 converged Fitting Repeat 4 # weights: 507 initial value 99.579609 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 107.260776 iter 10 value 86.079913 iter 20 value 84.238990 iter 30 value 84.189291 final value 84.189285 converged Fitting Repeat 1 # weights: 103 initial value 97.697348 iter 10 value 93.676171 iter 20 value 88.055346 iter 30 value 87.164092 iter 40 value 86.148788 iter 50 value 85.571312 iter 60 value 85.402397 iter 70 value 85.374819 iter 80 value 84.784341 iter 90 value 84.456206 final value 84.455512 converged Fitting Repeat 2 # weights: 103 initial value 100.062934 iter 10 value 93.452627 iter 20 value 86.637768 iter 30 value 85.661072 iter 40 value 85.429492 iter 50 value 84.817022 iter 60 value 84.467178 iter 70 value 84.457038 iter 70 value 84.457037 iter 70 value 84.457037 final value 84.457037 converged Fitting Repeat 3 # weights: 103 initial value 102.204029 iter 10 value 94.055665 iter 20 value 93.940827 iter 30 value 91.115921 iter 40 value 86.787784 iter 50 value 84.435963 iter 60 value 83.752162 final value 83.750479 converged Fitting Repeat 4 # weights: 103 initial value 96.247008 iter 10 value 94.046783 iter 20 value 93.466782 iter 30 value 91.094585 iter 40 value 89.334155 iter 50 value 84.382419 iter 60 value 82.848106 iter 70 value 82.574558 iter 80 value 81.704801 iter 90 value 81.186670 iter 100 value 81.000201 final value 81.000201 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 109.001909 iter 10 value 94.051550 iter 20 value 89.113277 iter 30 value 86.063248 iter 40 value 84.947856 iter 50 value 84.605349 iter 60 value 84.481716 iter 70 value 84.458666 final value 84.457662 converged Fitting Repeat 1 # weights: 305 initial value 103.870421 iter 10 value 94.083566 iter 20 value 86.468754 iter 30 value 85.510089 iter 40 value 85.313520 iter 50 value 83.949629 iter 60 value 83.082745 iter 70 value 82.459142 iter 80 value 82.339383 iter 90 value 81.884388 iter 100 value 81.542611 final value 81.542611 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 100.801960 iter 10 value 89.554731 iter 20 value 86.362905 iter 30 value 85.967018 iter 40 value 85.200071 iter 50 value 84.852351 iter 60 value 84.715598 iter 70 value 84.023505 iter 80 value 83.071832 iter 90 value 81.476724 iter 100 value 80.625681 final value 80.625681 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 111.763404 iter 10 value 94.071514 iter 20 value 93.901552 iter 30 value 87.737148 iter 40 value 85.158756 iter 50 value 81.643839 iter 60 value 80.355916 iter 70 value 80.233404 iter 80 value 80.081588 iter 90 value 79.981767 iter 100 value 79.971814 final value 79.971814 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 108.635782 iter 10 value 94.012383 iter 20 value 85.698576 iter 30 value 85.193930 iter 40 value 84.883757 iter 50 value 83.974802 iter 60 value 82.626368 iter 70 value 80.861145 iter 80 value 80.508231 iter 90 value 80.190063 iter 100 value 79.879351 final value 79.879351 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 118.410253 iter 10 value 94.056494 iter 20 value 86.661709 iter 30 value 85.434326 iter 40 value 84.910949 iter 50 value 82.800789 iter 60 value 80.984079 iter 70 value 80.633578 iter 80 value 80.479057 iter 90 value 80.211237 iter 100 value 79.593098 final value 79.593098 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 106.085533 iter 10 value 94.144315 iter 20 value 93.393640 iter 30 value 86.158300 iter 40 value 84.861216 iter 50 value 82.854811 iter 60 value 81.119280 iter 70 value 80.383678 iter 80 value 80.346767 iter 90 value 80.162396 iter 100 value 79.943004 final value 79.943004 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 112.071415 iter 10 value 94.202997 iter 20 value 93.959617 iter 30 value 85.488320 iter 40 value 85.253500 iter 50 value 84.477237 iter 60 value 81.819461 iter 70 value 81.555933 iter 80 value 81.073552 iter 90 value 79.694757 iter 100 value 79.255188 final value 79.255188 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 109.489753 iter 10 value 95.645192 iter 20 value 91.251972 iter 30 value 82.920848 iter 40 value 80.901957 iter 50 value 79.411634 iter 60 value 79.312578 iter 70 value 79.108004 iter 80 value 79.085607 iter 90 value 79.075768 iter 100 value 79.027997 final value 79.027997 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 127.549446 iter 10 value 93.802133 iter 20 value 93.112251 iter 30 value 91.820658 iter 40 value 87.111517 iter 50 value 85.016502 iter 60 value 81.778093 iter 70 value 80.941649 iter 80 value 80.537361 iter 90 value 80.317130 iter 100 value 79.958171 final value 79.958171 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 117.673866 iter 10 value 95.695156 iter 20 value 92.878002 iter 30 value 86.297955 iter 40 value 84.410091 iter 50 value 82.272849 iter 60 value 81.823375 iter 70 value 81.615196 iter 80 value 81.044415 iter 90 value 80.881551 iter 100 value 80.487324 final value 80.487324 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 100.306600 final value 94.054574 converged Fitting Repeat 2 # weights: 103 initial value 95.259669 iter 10 value 88.482588 iter 20 value 85.802291 final value 85.802217 converged Fitting Repeat 3 # weights: 103 initial value 95.504823 final value 94.010121 converged Fitting Repeat 4 # weights: 103 initial value 99.843179 final value 94.054501 converged Fitting Repeat 5 # weights: 103 initial value 94.988372 final value 94.054489 converged Fitting Repeat 1 # weights: 305 initial value 100.973243 iter 10 value 94.067603 iter 20 value 94.062006 iter 30 value 86.499190 iter 40 value 85.088924 iter 50 value 85.081457 iter 60 value 85.078429 final value 85.078111 converged Fitting Repeat 2 # weights: 305 initial value 97.846604 iter 10 value 94.057656 iter 20 value 93.419821 iter 30 value 87.798335 iter 40 value 87.340591 iter 50 value 87.330913 final value 87.330903 converged Fitting Repeat 3 # weights: 305 initial value 94.968548 iter 10 value 94.013551 iter 20 value 93.570476 iter 30 value 86.943933 iter 40 value 86.935733 iter 50 value 85.087353 iter 60 value 85.077832 final value 85.077747 converged Fitting Repeat 4 # weights: 305 initial value 112.419721 iter 10 value 94.057439 iter 20 value 94.051781 iter 30 value 86.975017 iter 40 value 86.609347 iter 50 value 84.988287 iter 60 value 84.984957 iter 70 value 84.945115 iter 80 value 84.939817 iter 90 value 84.622581 iter 100 value 84.537393 final value 84.537393 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 96.394710 iter 10 value 93.899024 iter 20 value 93.881534 final value 93.865610 converged Fitting Repeat 1 # weights: 507 initial value 102.151582 iter 10 value 94.061088 iter 20 value 94.042032 iter 30 value 92.265691 iter 40 value 87.908045 iter 50 value 86.446978 iter 60 value 86.216436 iter 70 value 86.209365 iter 80 value 83.981989 iter 90 value 82.686723 iter 100 value 82.682374 final value 82.682374 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 108.549979 iter 10 value 93.971270 iter 20 value 93.962793 iter 30 value 85.997330 iter 40 value 83.792041 iter 50 value 83.789689 iter 60 value 83.630456 iter 70 value 83.618374 iter 80 value 83.617710 final value 83.617378 converged Fitting Repeat 3 # weights: 507 initial value 105.745359 iter 10 value 94.016820 iter 20 value 94.010072 final value 94.009572 converged Fitting Repeat 4 # weights: 507 initial value 98.266248 iter 10 value 93.213734 iter 20 value 93.026788 iter 30 value 92.140793 iter 40 value 92.121611 iter 50 value 92.109279 final value 92.108915 converged Fitting Repeat 5 # weights: 507 initial value 98.974452 iter 10 value 85.319872 iter 20 value 84.089175 iter 30 value 83.777605 iter 40 value 83.142721 iter 50 value 83.007606 iter 60 value 83.003289 iter 70 value 83.003006 iter 80 value 82.921007 iter 90 value 81.744782 iter 100 value 80.010214 final value 80.010214 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 101.832237 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 98.836703 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 95.678701 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 105.345687 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 96.210491 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 98.956174 final value 94.354396 converged Fitting Repeat 2 # weights: 305 initial value 99.436360 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 95.620928 final value 94.484210 converged Fitting Repeat 4 # weights: 305 initial value 102.063293 iter 10 value 94.038286 iter 20 value 88.360965 iter 30 value 88.212123 final value 88.212121 converged Fitting Repeat 5 # weights: 305 initial value 96.432076 final value 94.354396 converged Fitting Repeat 1 # weights: 507 initial value 95.305140 final value 94.354396 converged Fitting Repeat 2 # weights: 507 initial value 97.552605 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 106.306819 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 96.340026 final value 93.936782 converged Fitting Repeat 5 # weights: 507 initial value 106.421091 iter 10 value 94.321437 final value 94.321429 converged Fitting Repeat 1 # weights: 103 initial value 99.683838 iter 10 value 94.456570 iter 20 value 86.741298 iter 30 value 84.897521 iter 40 value 84.601126 iter 50 value 84.527888 iter 60 value 84.358110 iter 70 value 84.149988 final value 84.141204 converged Fitting Repeat 2 # weights: 103 initial value 101.163200 iter 10 value 94.475032 iter 20 value 94.000569 iter 30 value 88.746432 iter 40 value 87.912191 iter 50 value 83.831460 iter 60 value 83.648325 iter 70 value 82.448931 iter 80 value 82.248046 iter 90 value 82.027059 iter 100 value 82.024818 final value 82.024818 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 98.615422 iter 10 value 94.297475 iter 20 value 94.178805 iter 30 value 85.339743 iter 40 value 84.278219 iter 50 value 84.086137 iter 60 value 83.770466 iter 70 value 83.737886 final value 83.737883 converged Fitting Repeat 4 # weights: 103 initial value 96.370226 iter 10 value 94.462699 iter 20 value 93.475758 iter 30 value 89.508312 iter 40 value 88.235765 iter 50 value 86.510664 iter 60 value 84.570834 iter 70 value 82.601155 iter 80 value 82.066442 iter 90 value 82.025935 iter 100 value 82.024830 final value 82.024830 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 98.451793 iter 10 value 94.474345 iter 20 value 91.038015 iter 30 value 85.013930 iter 40 value 84.532345 iter 50 value 84.355547 iter 60 value 84.194069 iter 70 value 84.144043 iter 80 value 84.141763 iter 90 value 84.140830 iter 90 value 84.140830 iter 90 value 84.140830 final value 84.140830 converged Fitting Repeat 1 # weights: 305 initial value 115.470372 iter 10 value 94.430920 iter 20 value 90.701118 iter 30 value 85.696927 iter 40 value 84.633313 iter 50 value 83.919342 iter 60 value 83.373136 iter 70 value 82.723818 iter 80 value 81.881994 iter 90 value 81.712228 iter 100 value 81.471470 final value 81.471470 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 100.354593 iter 10 value 94.121536 iter 20 value 92.719563 iter 30 value 87.684566 iter 40 value 86.597422 iter 50 value 84.383481 iter 60 value 83.388352 iter 70 value 81.955678 iter 80 value 81.437637 iter 90 value 81.219718 iter 100 value 81.115360 final value 81.115360 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 108.520233 iter 10 value 94.643224 iter 20 value 94.518849 iter 30 value 84.959251 iter 40 value 84.151411 iter 50 value 83.829869 iter 60 value 83.651067 iter 70 value 82.424048 iter 80 value 81.840615 iter 90 value 81.524571 iter 100 value 81.337277 final value 81.337277 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 103.272857 iter 10 value 94.426945 iter 20 value 86.643280 iter 30 value 84.735141 iter 40 value 84.250877 iter 50 value 84.046391 iter 60 value 83.853004 iter 70 value 83.295032 iter 80 value 82.286712 iter 90 value 81.349479 iter 100 value 81.191019 final value 81.191019 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 113.515325 iter 10 value 94.486917 iter 20 value 93.951713 iter 30 value 90.789447 iter 40 value 90.557930 iter 50 value 89.720930 iter 60 value 84.859173 iter 70 value 83.011612 iter 80 value 82.315697 iter 90 value 82.197156 iter 100 value 81.848792 final value 81.848792 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 107.264086 iter 10 value 94.545759 iter 20 value 88.892381 iter 30 value 87.632011 iter 40 value 85.827633 iter 50 value 84.509554 iter 60 value 84.225296 iter 70 value 83.870898 iter 80 value 83.769816 iter 90 value 82.640773 iter 100 value 82.457419 final value 82.457419 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 117.384773 iter 10 value 95.015547 iter 20 value 90.553009 iter 30 value 86.373311 iter 40 value 85.746427 iter 50 value 84.457519 iter 60 value 82.260196 iter 70 value 81.335157 iter 80 value 81.116279 iter 90 value 80.816904 iter 100 value 80.630091 final value 80.630091 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 135.976423 iter 10 value 94.240419 iter 20 value 86.070324 iter 30 value 84.011937 iter 40 value 82.398311 iter 50 value 81.780565 iter 60 value 81.630107 iter 70 value 81.501156 iter 80 value 81.381894 iter 90 value 81.124534 iter 100 value 81.102919 final value 81.102919 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 105.228378 iter 10 value 94.593521 iter 20 value 88.245963 iter 30 value 87.191338 iter 40 value 85.299017 iter 50 value 83.548298 iter 60 value 82.662190 iter 70 value 82.283481 iter 80 value 82.225081 iter 90 value 81.876163 iter 100 value 81.837699 final value 81.837699 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 142.413229 iter 10 value 96.126102 iter 20 value 94.475425 iter 30 value 93.527668 iter 40 value 89.456145 iter 50 value 86.075730 iter 60 value 83.597001 iter 70 value 82.747476 iter 80 value 82.605828 iter 90 value 82.220795 iter 100 value 81.511970 final value 81.511970 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.221355 iter 10 value 94.485912 final value 94.485762 converged Fitting Repeat 2 # weights: 103 initial value 100.744141 final value 94.485902 converged Fitting Repeat 3 # weights: 103 initial value 98.384338 final value 94.485674 converged Fitting Repeat 4 # weights: 103 initial value 97.601244 final value 94.485906 converged Fitting Repeat 5 # weights: 103 initial value 95.315493 iter 10 value 94.485980 iter 20 value 94.484256 final value 94.484215 converged Fitting Repeat 1 # weights: 305 initial value 108.905097 iter 10 value 94.484678 iter 20 value 88.128464 iter 30 value 84.186146 iter 40 value 82.069161 iter 50 value 81.881317 final value 81.879942 converged Fitting Repeat 2 # weights: 305 initial value 104.918936 iter 10 value 94.488852 iter 20 value 94.477269 iter 30 value 93.240103 iter 40 value 93.220807 iter 50 value 91.801132 iter 60 value 82.795465 iter 70 value 82.764631 iter 80 value 81.987048 iter 90 value 81.212592 iter 100 value 80.374945 final value 80.374945 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 106.870578 iter 10 value 94.493362 iter 20 value 94.470810 iter 30 value 85.670697 iter 40 value 85.663454 iter 50 value 85.661012 iter 60 value 85.570635 iter 70 value 84.213185 iter 80 value 84.210260 iter 90 value 83.168231 iter 100 value 81.065943 final value 81.065943 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.993316 iter 10 value 94.525018 iter 20 value 94.411725 iter 30 value 92.341502 iter 40 value 92.309290 iter 50 value 91.553017 iter 60 value 91.542413 iter 70 value 91.534760 iter 80 value 91.434396 iter 90 value 91.397234 iter 100 value 91.392532 final value 91.392532 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 109.977072 iter 10 value 93.863979 iter 20 value 93.823197 iter 30 value 85.791981 iter 40 value 85.285523 iter 50 value 85.285418 iter 60 value 85.285205 final value 85.285201 converged Fitting Repeat 1 # weights: 507 initial value 111.822317 iter 10 value 94.492292 iter 20 value 94.457288 iter 30 value 90.819205 iter 40 value 86.922725 iter 50 value 82.802568 iter 60 value 82.463128 iter 70 value 82.371910 final value 82.371003 converged Fitting Repeat 2 # weights: 507 initial value 107.083651 iter 10 value 94.467358 iter 20 value 94.362047 iter 30 value 94.361320 iter 40 value 94.356005 iter 50 value 92.357337 iter 60 value 84.439552 iter 70 value 83.890666 iter 80 value 83.231321 iter 90 value 83.043487 iter 100 value 81.112024 final value 81.112024 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 113.492082 iter 10 value 94.492310 iter 20 value 94.484282 iter 30 value 89.392541 final value 89.392201 converged Fitting Repeat 4 # weights: 507 initial value 97.449875 iter 10 value 94.362259 iter 20 value 94.354513 final value 94.354447 converged Fitting Repeat 5 # weights: 507 initial value 102.668162 iter 10 value 94.054982 iter 20 value 94.049099 iter 30 value 94.048925 iter 40 value 90.657423 iter 50 value 87.133723 iter 60 value 83.937298 final value 83.937296 converged Fitting Repeat 1 # weights: 103 initial value 94.266634 iter 10 value 89.894497 iter 20 value 88.223699 iter 30 value 88.124156 iter 40 value 88.107567 final value 88.107560 converged Fitting Repeat 2 # weights: 103 initial value 104.442735 final value 94.305880 converged Fitting Repeat 3 # weights: 103 initial value 101.757324 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 102.392424 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 98.424376 iter 10 value 94.113855 final value 94.112570 converged Fitting Repeat 1 # weights: 305 initial value 98.431977 final value 94.428839 converged Fitting Repeat 2 # weights: 305 initial value 101.767895 final value 94.322897 converged Fitting Repeat 3 # weights: 305 initial value 105.272119 final value 94.322897 converged Fitting Repeat 4 # weights: 305 initial value 98.035273 final value 94.354396 converged Fitting Repeat 5 # weights: 305 initial value 107.495067 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 104.600327 iter 10 value 94.275572 final value 94.275362 converged Fitting Repeat 2 # weights: 507 initial value 106.580110 iter 10 value 94.289216 iter 10 value 94.289216 iter 10 value 94.289216 final value 94.289216 converged Fitting Repeat 3 # weights: 507 initial value 96.399536 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 102.414046 iter 10 value 90.308433 iter 20 value 90.295092 final value 90.295083 converged Fitting Repeat 5 # weights: 507 initial value 99.361654 iter 10 value 87.508419 iter 20 value 86.384247 final value 86.384048 converged Fitting Repeat 1 # weights: 103 initial value 113.619698 iter 10 value 94.254306 iter 20 value 88.430369 iter 30 value 84.958706 iter 40 value 83.709439 iter 50 value 83.204480 iter 60 value 82.837425 iter 70 value 82.688145 iter 80 value 82.442010 iter 90 value 82.074844 iter 100 value 82.066627 final value 82.066627 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 102.136777 iter 10 value 93.961257 iter 20 value 90.784405 iter 30 value 88.396147 iter 40 value 85.760480 iter 50 value 85.442809 iter 60 value 83.054663 iter 70 value 82.663066 iter 80 value 82.648501 final value 82.648498 converged Fitting Repeat 3 # weights: 103 initial value 101.414706 iter 10 value 94.486104 iter 20 value 94.050695 iter 30 value 93.006518 iter 40 value 92.728404 iter 50 value 90.473865 iter 60 value 86.171541 iter 70 value 84.676645 iter 80 value 84.596172 iter 90 value 84.549369 iter 100 value 84.531128 final value 84.531128 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 105.521056 iter 10 value 94.489159 iter 20 value 94.485897 iter 30 value 88.696654 iter 40 value 88.237553 iter 50 value 85.993421 iter 60 value 83.401637 iter 70 value 83.331040 iter 80 value 83.274766 final value 83.273719 converged Fitting Repeat 5 # weights: 103 initial value 112.609230 iter 10 value 93.176789 iter 20 value 88.326358 iter 30 value 85.080970 iter 40 value 84.715381 iter 50 value 84.535318 iter 60 value 84.530325 final value 84.529818 converged Fitting Repeat 1 # weights: 305 initial value 105.892917 iter 10 value 94.481926 iter 20 value 89.874970 iter 30 value 85.451372 iter 40 value 84.318704 iter 50 value 82.158355 iter 60 value 80.755411 iter 70 value 80.386472 iter 80 value 80.338260 iter 90 value 79.747307 iter 100 value 79.418687 final value 79.418687 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 104.319067 iter 10 value 95.277446 iter 20 value 91.942377 iter 30 value 85.974908 iter 40 value 85.122079 iter 50 value 83.645160 iter 60 value 82.534712 iter 70 value 80.933143 iter 80 value 80.447326 iter 90 value 79.788315 iter 100 value 79.265432 final value 79.265432 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 103.734807 iter 10 value 94.310258 iter 20 value 89.581235 iter 30 value 84.489989 iter 40 value 83.480781 iter 50 value 81.691830 iter 60 value 80.740379 iter 70 value 79.737008 iter 80 value 79.643275 iter 90 value 79.599190 iter 100 value 79.586924 final value 79.586924 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 110.858948 iter 10 value 94.423398 iter 20 value 91.639102 iter 30 value 90.905132 iter 40 value 86.616124 iter 50 value 84.571056 iter 60 value 82.787064 iter 70 value 81.891179 iter 80 value 81.060022 iter 90 value 80.376533 iter 100 value 79.618900 final value 79.618900 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 104.269904 iter 10 value 94.507161 iter 20 value 94.197952 iter 30 value 89.629883 iter 40 value 89.092123 iter 50 value 88.193997 iter 60 value 86.431933 iter 70 value 85.793035 iter 80 value 85.604648 iter 90 value 85.593914 iter 100 value 82.445119 final value 82.445119 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 103.195851 iter 10 value 94.792015 iter 20 value 87.857603 iter 30 value 82.888124 iter 40 value 82.113984 iter 50 value 81.515007 iter 60 value 81.366068 iter 70 value 80.748735 iter 80 value 80.043432 iter 90 value 79.866043 iter 100 value 79.587517 final value 79.587517 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 117.155144 iter 10 value 94.140885 iter 20 value 86.684403 iter 30 value 84.046734 iter 40 value 80.577339 iter 50 value 80.029895 iter 60 value 79.538801 iter 70 value 79.488093 iter 80 value 79.420527 iter 90 value 79.189620 iter 100 value 78.812306 final value 78.812306 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 104.917132 iter 10 value 94.667724 iter 20 value 93.937231 iter 30 value 92.108470 iter 40 value 91.168980 iter 50 value 89.907438 iter 60 value 87.381741 iter 70 value 84.434061 iter 80 value 82.360093 iter 90 value 81.515387 iter 100 value 81.123035 final value 81.123035 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 109.179857 iter 10 value 94.471012 iter 20 value 88.531948 iter 30 value 85.995944 iter 40 value 82.493298 iter 50 value 80.981328 iter 60 value 80.272757 iter 70 value 80.077659 iter 80 value 79.757128 iter 90 value 79.563712 iter 100 value 79.466686 final value 79.466686 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 121.920970 iter 10 value 94.688895 iter 20 value 94.310235 iter 30 value 91.562617 iter 40 value 87.208192 iter 50 value 84.528370 iter 60 value 82.435673 iter 70 value 79.909463 iter 80 value 79.386254 iter 90 value 79.063524 iter 100 value 78.867784 final value 78.867784 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.313534 iter 10 value 94.485673 final value 94.484220 converged Fitting Repeat 2 # weights: 103 initial value 102.480341 iter 10 value 94.486028 iter 20 value 94.484222 iter 30 value 94.120884 iter 40 value 94.112837 final value 94.112823 converged Fitting Repeat 3 # weights: 103 initial value 99.262209 iter 10 value 94.485869 iter 20 value 94.305965 iter 30 value 91.197769 iter 40 value 91.171940 iter 50 value 90.194823 iter 60 value 89.331024 iter 70 value 89.255792 iter 80 value 89.251431 iter 90 value 87.549658 iter 100 value 87.233190 final value 87.233190 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 97.509023 final value 94.485745 converged Fitting Repeat 5 # weights: 103 initial value 98.220721 final value 94.485816 converged Fitting Repeat 1 # weights: 305 initial value 120.748212 iter 10 value 94.359242 iter 20 value 94.355882 final value 94.355796 converged Fitting Repeat 2 # weights: 305 initial value 104.242418 iter 10 value 94.489153 iter 20 value 94.484219 iter 20 value 94.484218 iter 20 value 94.484218 final value 94.484218 converged Fitting Repeat 3 # weights: 305 initial value 105.498569 iter 10 value 94.488833 iter 20 value 94.484230 final value 94.354680 converged Fitting Repeat 4 # weights: 305 initial value 109.912371 iter 10 value 94.327764 iter 20 value 89.714984 iter 30 value 87.260586 iter 40 value 86.450813 iter 50 value 86.378451 iter 50 value 86.378451 iter 50 value 86.378451 final value 86.378451 converged Fitting Repeat 5 # weights: 305 initial value 102.972283 iter 10 value 94.489258 iter 20 value 94.302525 iter 30 value 92.898825 iter 40 value 90.584457 iter 50 value 90.546068 iter 60 value 90.545911 iter 70 value 90.509170 iter 80 value 90.026849 iter 90 value 89.429224 iter 100 value 89.251692 final value 89.251692 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 100.687372 iter 10 value 94.361904 iter 20 value 92.330003 iter 30 value 81.639640 iter 40 value 81.631129 iter 50 value 81.620956 iter 60 value 81.613041 iter 70 value 81.525356 iter 80 value 80.177571 iter 90 value 80.005881 iter 100 value 80.005177 final value 80.005177 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 104.448114 iter 10 value 94.489205 iter 20 value 91.961028 iter 30 value 85.671424 iter 40 value 85.661962 iter 50 value 85.648376 iter 60 value 85.546364 iter 70 value 85.544401 iter 80 value 85.406575 iter 90 value 85.331611 iter 100 value 85.331413 final value 85.331413 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 104.004442 iter 10 value 94.492111 iter 20 value 94.484535 iter 30 value 94.067907 iter 40 value 90.078247 iter 50 value 89.952028 iter 60 value 87.224082 final value 86.055141 converged Fitting Repeat 4 # weights: 507 initial value 104.710430 iter 10 value 94.491484 iter 20 value 94.369535 iter 30 value 89.030911 iter 40 value 83.594640 final value 83.594449 converged Fitting Repeat 5 # weights: 507 initial value 99.870826 iter 10 value 94.492609 iter 20 value 94.483779 iter 30 value 85.005351 iter 40 value 84.752235 iter 50 value 84.750307 iter 60 value 84.051641 iter 70 value 83.904752 iter 80 value 83.458293 final value 83.458265 converged Fitting Repeat 1 # weights: 507 initial value 129.393698 iter 10 value 117.688441 iter 20 value 117.686305 iter 30 value 117.539904 iter 40 value 117.539498 iter 50 value 117.537997 iter 60 value 112.366086 iter 70 value 105.444626 iter 80 value 104.794344 iter 90 value 104.747321 iter 100 value 101.931127 final value 101.931127 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 121.576885 iter 10 value 117.767062 iter 20 value 117.759117 iter 30 value 117.520080 iter 40 value 114.904989 iter 50 value 112.080041 iter 60 value 111.987071 iter 70 value 110.813096 iter 80 value 110.517568 iter 90 value 110.489552 iter 100 value 105.577500 final value 105.577500 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 140.105258 iter 10 value 117.131149 iter 20 value 117.103842 iter 30 value 111.744098 iter 40 value 108.430546 iter 50 value 108.426163 iter 60 value 108.413840 iter 70 value 108.413224 iter 80 value 108.092837 final value 108.092609 converged Fitting Repeat 4 # weights: 507 initial value 118.395216 iter 10 value 117.767458 iter 20 value 117.743882 iter 30 value 117.728773 iter 40 value 117.728631 iter 50 value 117.728591 iter 60 value 117.728528 iter 70 value 117.728467 iter 80 value 115.598112 iter 90 value 106.944418 iter 100 value 106.649963 final value 106.649963 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 123.359161 iter 10 value 117.898063 iter 20 value 117.890285 iter 30 value 107.706854 iter 40 value 107.002344 iter 50 value 106.779352 iter 60 value 106.779016 iter 70 value 106.777350 iter 80 value 106.655642 final value 106.655576 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 8 21:45:31 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 43.079 1.741 126.097
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 33.582 | 1.839 | 35.764 | |
FreqInteractors | 0.256 | 0.013 | 0.272 | |
calculateAAC | 0.039 | 0.010 | 0.049 | |
calculateAutocor | 0.363 | 0.070 | 0.438 | |
calculateCTDC | 0.084 | 0.006 | 0.090 | |
calculateCTDD | 0.651 | 0.022 | 0.677 | |
calculateCTDT | 0.223 | 0.011 | 0.236 | |
calculateCTriad | 0.378 | 0.040 | 0.423 | |
calculateDC | 0.103 | 0.011 | 0.116 | |
calculateF | 0.364 | 0.013 | 0.378 | |
calculateKSAAP | 0.102 | 0.009 | 0.111 | |
calculateQD_Sm | 1.739 | 0.124 | 1.883 | |
calculateTC | 2.011 | 0.165 | 2.198 | |
calculateTC_Sm | 0.235 | 0.015 | 0.252 | |
corr_plot | 33.665 | 1.875 | 35.919 | |
enrichfindP | 0.467 | 0.057 | 8.220 | |
enrichfind_hp | 0.057 | 0.022 | 1.011 | |
enrichplot | 0.405 | 0.010 | 0.417 | |
filter_missing_values | 0.001 | 0.000 | 0.001 | |
getFASTA | 0.068 | 0.011 | 3.009 | |
getHPI | 0.000 | 0.000 | 0.001 | |
get_negativePPI | 0.001 | 0.000 | 0.001 | |
get_positivePPI | 0.001 | 0.000 | 0.000 | |
impute_missing_data | 0.001 | 0.000 | 0.001 | |
plotPPI | 0.072 | 0.003 | 0.075 | |
pred_ensembel | 13.964 | 0.451 | 12.456 | |
var_imp | 35.827 | 2.083 | 38.507 | |