Back to Multiple platform build/check report for BioC 3.19: simplified long |
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This page was generated on 2024-06-25 17:43 -0400 (Tue, 25 Jun 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4760 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 (2024-04-24 ucrt) -- "Puppy Cup" | 4494 |
merida1 | macOS 12.7.4 Monterey | x86_64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4508 |
kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.0 (2024-04-24) -- "Puppy Cup" | 4466 |
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 987/2300 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
HPiP 1.10.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | ![]() | ||||||||
palomino3 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | ![]() | ||||||||
merida1 | macOS 12.7.4 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kjohnson1 | macOS 13.6.6 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: 1.10.0 |
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_1.10.0.tar.gz |
StartedAt: 2024-06-24 22:45:20 -0400 (Mon, 24 Jun 2024) |
EndedAt: 2024-06-24 22:50:59 -0400 (Mon, 24 Jun 2024) |
EllapsedTime: 338.2 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_1.10.0.tar.gz ### ############################################################################## ############################################################################## * using log directory ‘/Users/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’ * using R version 4.4.0 (2024-04-24) * using platform: aarch64-apple-darwin20 * R was compiled by Apple clang version 14.0.0 (clang-1400.0.29.202) GNU Fortran (GCC) 12.2.0 * running under: macOS Ventura 13.6.6 * using session charset: UTF-8 * using option ‘--no-vignettes’ * checking for file ‘HPiP/DESCRIPTION’ ... OK * checking extension type ... Package * this is package ‘HPiP’ version ‘1.10.0’ * 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 ... NOTE 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 55.465 1.999 57.512 FSmethod 52.348 1.959 54.420 corr_plot 51.733 2.133 53.981 pred_ensembel 16.028 0.320 13.575 enrichfindP 0.462 0.073 7.870 * 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: 3 NOTEs See ‘/Users/biocbuild/bbs-3.19-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/4.4-arm64/Resources/library’ * installing *source* package ‘HPiP’ ... ** 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 4.4.0 (2024-04-24) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: aarch64-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 101.855268 iter 10 value 94.013956 iter 20 value 93.610297 iter 30 value 90.643440 iter 30 value 90.643440 iter 30 value 90.643440 final value 90.643440 converged Fitting Repeat 2 # weights: 103 initial value 94.460530 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 96.484598 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 96.389589 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 97.777053 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 95.861574 final value 93.582418 converged Fitting Repeat 2 # weights: 305 initial value 113.399766 iter 10 value 93.582421 final value 93.582418 converged Fitting Repeat 3 # weights: 305 initial value 96.299720 iter 10 value 93.582418 iter 10 value 93.582418 iter 10 value 93.582418 final value 93.582418 converged Fitting Repeat 4 # weights: 305 initial value 104.950365 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 118.053711 final value 93.582418 converged Fitting Repeat 1 # weights: 507 initial value 100.670134 final value 94.052910 converged Fitting Repeat 2 # weights: 507 initial value 104.072236 iter 10 value 93.582418 iter 10 value 93.582418 iter 10 value 93.582418 final value 93.582418 converged Fitting Repeat 3 # weights: 507 initial value 96.226130 iter 10 value 93.582417 iter 10 value 93.582417 iter 10 value 93.582417 final value 93.582417 converged Fitting Repeat 4 # weights: 507 initial value 106.135728 iter 10 value 93.582429 final value 93.582418 converged Fitting Repeat 5 # weights: 507 initial value 93.710159 iter 10 value 91.801808 iter 20 value 90.415675 iter 30 value 90.136860 iter 40 value 89.857114 final value 89.856915 converged Fitting Repeat 1 # weights: 103 initial value 127.710400 iter 10 value 90.559966 iter 20 value 88.558361 iter 30 value 86.401700 iter 40 value 84.037149 iter 50 value 83.786940 iter 60 value 83.514145 iter 70 value 83.462696 final value 83.459097 converged Fitting Repeat 2 # weights: 103 initial value 113.436308 iter 10 value 93.982956 iter 20 value 90.347075 iter 30 value 88.073997 iter 40 value 87.342525 iter 50 value 87.038995 iter 60 value 85.879918 iter 70 value 85.355480 iter 80 value 85.351007 final value 85.351005 converged Fitting Repeat 3 # weights: 103 initial value 100.420331 iter 10 value 93.752236 iter 20 value 93.415874 iter 30 value 87.549248 iter 40 value 85.886726 iter 50 value 83.396921 iter 60 value 83.357165 iter 70 value 83.204587 iter 80 value 83.167439 iter 90 value 83.027659 iter 100 value 83.016310 final value 83.016310 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 98.137410 iter 10 value 94.057433 iter 20 value 94.056604 iter 30 value 90.769906 iter 40 value 85.309100 iter 50 value 84.388690 iter 60 value 83.942417 iter 70 value 83.774306 iter 80 value 83.587875 iter 90 value 83.575448 final value 83.575440 converged Fitting Repeat 5 # weights: 103 initial value 98.029874 iter 10 value 94.056163 iter 20 value 93.850858 iter 30 value 93.634405 iter 40 value 93.628658 iter 50 value 93.622280 iter 60 value 92.940154 iter 70 value 85.233104 iter 80 value 84.769886 iter 90 value 83.982925 iter 100 value 83.823453 final value 83.823453 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 102.149383 iter 10 value 94.048061 iter 20 value 90.186207 iter 30 value 84.845605 iter 40 value 82.116951 iter 50 value 81.894088 iter 60 value 81.121727 iter 70 value 80.055179 iter 80 value 79.659488 iter 90 value 79.487879 iter 100 value 79.383250 final value 79.383250 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 101.960872 iter 10 value 94.164945 iter 20 value 91.203364 iter 30 value 86.052571 iter 40 value 84.486853 iter 50 value 81.689743 iter 60 value 80.555922 iter 70 value 80.432306 iter 80 value 80.358597 iter 90 value 80.087119 iter 100 value 79.897650 final value 79.897650 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 113.862983 iter 10 value 94.247383 iter 20 value 93.820117 iter 30 value 92.178092 iter 40 value 87.024612 iter 50 value 83.843395 iter 60 value 82.057528 iter 70 value 80.450635 iter 80 value 80.118744 iter 90 value 79.799933 iter 100 value 79.728212 final value 79.728212 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 101.632865 iter 10 value 94.096924 iter 20 value 91.231462 iter 30 value 86.025189 iter 40 value 84.195283 iter 50 value 83.155501 iter 60 value 81.789064 iter 70 value 80.907741 iter 80 value 80.673457 iter 90 value 80.554868 iter 100 value 80.462282 final value 80.462282 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 109.490665 iter 10 value 93.751629 iter 20 value 86.491257 iter 30 value 85.157701 iter 40 value 83.780498 iter 50 value 83.455279 iter 60 value 83.263860 iter 70 value 81.545262 iter 80 value 80.640043 iter 90 value 80.275134 iter 100 value 80.078538 final value 80.078538 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 123.606982 iter 10 value 94.014858 iter 20 value 88.942396 iter 30 value 85.859079 iter 40 value 85.678021 iter 50 value 85.363938 iter 60 value 84.802836 iter 70 value 83.326780 iter 80 value 81.909658 iter 90 value 81.493763 iter 100 value 80.604855 final value 80.604855 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 105.729170 iter 10 value 95.562232 iter 20 value 91.847799 iter 30 value 88.524854 iter 40 value 87.765827 iter 50 value 86.331021 iter 60 value 83.685610 iter 70 value 81.735194 iter 80 value 80.622664 iter 90 value 80.202976 iter 100 value 79.894167 final value 79.894167 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 103.860767 iter 10 value 94.949072 iter 20 value 92.383065 iter 30 value 88.517645 iter 40 value 87.176976 iter 50 value 84.419187 iter 60 value 81.554217 iter 70 value 80.544475 iter 80 value 80.239577 iter 90 value 80.150787 iter 100 value 79.826135 final value 79.826135 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 128.348942 iter 10 value 94.026842 iter 20 value 93.680532 iter 30 value 87.383077 iter 40 value 86.783965 iter 50 value 85.104055 iter 60 value 82.076985 iter 70 value 81.350916 iter 80 value 80.688176 iter 90 value 80.273968 iter 100 value 80.192309 final value 80.192309 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 110.030301 iter 10 value 97.188092 iter 20 value 93.296571 iter 30 value 89.724080 iter 40 value 85.959037 iter 50 value 83.284685 iter 60 value 82.503054 iter 70 value 82.213242 iter 80 value 81.958799 iter 90 value 81.851819 iter 100 value 81.394674 final value 81.394674 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 100.676514 iter 10 value 94.054321 iter 20 value 93.883280 iter 30 value 88.885969 iter 40 value 88.842349 iter 50 value 87.911217 iter 60 value 87.903796 final value 87.903790 converged Fitting Repeat 2 # weights: 103 initial value 101.769209 final value 94.054458 converged Fitting Repeat 3 # weights: 103 initial value 100.031943 final value 94.054618 converged Fitting Repeat 4 # weights: 103 initial value 100.088762 iter 10 value 94.054640 iter 20 value 94.038770 final value 93.584080 converged Fitting Repeat 5 # weights: 103 initial value 94.784892 final value 94.054001 converged Fitting Repeat 1 # weights: 305 initial value 120.333360 iter 10 value 94.057964 iter 20 value 92.919459 iter 30 value 92.547694 iter 40 value 89.969713 iter 50 value 89.964385 final value 89.964322 converged Fitting Repeat 2 # weights: 305 initial value 95.101760 iter 10 value 94.057212 iter 20 value 94.048682 iter 30 value 90.939704 iter 40 value 90.878915 iter 50 value 89.927615 final value 89.883590 converged Fitting Repeat 3 # weights: 305 initial value 95.072049 iter 10 value 94.057768 iter 20 value 94.052901 iter 30 value 85.247592 iter 40 value 85.225929 iter 50 value 85.225286 iter 60 value 85.103184 iter 70 value 84.821128 iter 80 value 82.479566 iter 90 value 82.341258 iter 100 value 81.658905 final value 81.658905 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 96.580646 iter 10 value 94.057241 iter 20 value 93.605518 final value 93.605215 converged Fitting Repeat 5 # weights: 305 initial value 104.952104 iter 10 value 93.587809 iter 20 value 93.582763 iter 30 value 93.568654 iter 40 value 86.766018 iter 50 value 86.764707 iter 60 value 85.871084 iter 70 value 82.582122 iter 80 value 82.453403 iter 90 value 82.437597 final value 82.437569 converged Fitting Repeat 1 # weights: 507 initial value 102.589423 iter 10 value 93.591142 iter 20 value 93.456399 iter 30 value 86.641564 iter 40 value 86.340858 iter 50 value 85.062364 iter 60 value 84.514808 iter 70 value 83.673845 iter 80 value 83.672740 final value 83.672558 converged Fitting Repeat 2 # weights: 507 initial value 102.032575 iter 10 value 90.501594 iter 20 value 87.936011 iter 30 value 87.919140 iter 40 value 86.689662 iter 50 value 85.410293 iter 60 value 82.959656 iter 70 value 80.284352 iter 80 value 79.716018 iter 90 value 79.691454 iter 100 value 79.672986 final value 79.672986 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 101.042772 iter 10 value 93.868682 iter 20 value 93.589590 iter 30 value 93.580537 final value 93.580085 converged Fitting Repeat 4 # weights: 507 initial value 128.798697 iter 10 value 94.061125 iter 20 value 94.052931 iter 30 value 93.582790 final value 93.582783 converged Fitting Repeat 5 # weights: 507 initial value 102.989697 iter 10 value 94.063193 iter 20 value 94.054148 iter 30 value 88.668453 iter 40 value 86.951370 iter 50 value 86.943387 iter 60 value 86.942549 iter 70 value 86.939416 iter 80 value 85.203340 iter 90 value 85.116492 final value 85.116425 converged Fitting Repeat 1 # weights: 103 initial value 100.394661 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 95.499885 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 98.768070 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 96.839505 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 95.786488 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 94.927958 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 103.555014 final value 93.915746 converged Fitting Repeat 3 # weights: 305 initial value 102.745987 final value 93.587879 converged Fitting Repeat 4 # weights: 305 initial value 95.924991 final value 93.915746 converged Fitting Repeat 5 # weights: 305 initial value 118.682134 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 110.811435 final value 93.604520 converged Fitting Repeat 2 # weights: 507 initial value 100.009189 iter 10 value 89.452864 iter 20 value 84.976818 iter 30 value 84.955826 iter 40 value 84.738693 final value 84.738619 converged Fitting Repeat 3 # weights: 507 initial value 112.113202 iter 10 value 93.656596 iter 10 value 93.656596 iter 10 value 93.656596 final value 93.656596 converged Fitting Repeat 4 # weights: 507 initial value 96.259235 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 119.843496 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 103.299076 iter 10 value 94.017548 iter 20 value 93.164449 iter 30 value 92.232214 iter 40 value 87.926142 iter 50 value 83.650674 iter 60 value 82.488241 iter 70 value 82.030510 iter 80 value 81.081670 iter 90 value 80.873468 iter 100 value 80.732137 final value 80.732137 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 95.902839 iter 10 value 94.057315 iter 20 value 93.973043 iter 30 value 93.943899 iter 40 value 89.302508 iter 50 value 83.801180 iter 60 value 83.472108 iter 70 value 82.714315 iter 80 value 82.383523 iter 90 value 82.311398 final value 82.311358 converged Fitting Repeat 3 # weights: 103 initial value 99.257261 iter 10 value 94.106307 iter 20 value 94.039501 iter 30 value 92.648257 iter 40 value 90.787727 iter 50 value 89.659995 iter 60 value 89.256073 iter 70 value 89.239013 iter 80 value 89.237201 iter 90 value 89.236034 iter 100 value 89.217280 final value 89.217280 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 102.264822 iter 10 value 93.966950 iter 20 value 93.702042 iter 30 value 93.137986 iter 40 value 90.784426 iter 50 value 83.589063 iter 60 value 83.492791 iter 70 value 83.266594 iter 80 value 82.807045 iter 90 value 82.501609 iter 100 value 81.149391 final value 81.149391 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 96.502779 iter 10 value 94.054173 iter 20 value 84.405314 iter 30 value 83.779098 iter 40 value 83.503070 iter 50 value 82.981239 iter 60 value 82.571418 iter 70 value 82.538004 iter 80 value 82.374547 iter 90 value 82.311703 iter 100 value 82.311098 final value 82.311098 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 99.913885 iter 10 value 94.038581 iter 20 value 92.575310 iter 30 value 86.439362 iter 40 value 83.415510 iter 50 value 82.109385 iter 60 value 81.153512 iter 70 value 80.029348 iter 80 value 79.737490 iter 90 value 79.606627 iter 100 value 79.593617 final value 79.593617 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 128.355751 iter 10 value 94.120425 iter 20 value 91.375510 iter 30 value 90.722570 iter 40 value 90.263449 iter 50 value 90.041935 iter 60 value 89.806222 iter 70 value 89.540012 iter 80 value 86.307760 iter 90 value 83.032704 iter 100 value 82.701865 final value 82.701865 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.752045 iter 10 value 94.027360 iter 20 value 92.469164 iter 30 value 89.090667 iter 40 value 87.207332 iter 50 value 83.514304 iter 60 value 82.977324 iter 70 value 82.334358 iter 80 value 82.264751 iter 90 value 82.084467 iter 100 value 81.176619 final value 81.176619 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 99.774557 iter 10 value 94.111784 iter 20 value 93.837333 iter 30 value 93.645109 iter 40 value 88.820536 iter 50 value 83.834772 iter 60 value 80.476075 iter 70 value 80.149886 iter 80 value 79.843779 iter 90 value 79.707471 iter 100 value 79.704688 final value 79.704688 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 109.185837 iter 10 value 93.848878 iter 20 value 89.587699 iter 30 value 85.775702 iter 40 value 85.533875 iter 50 value 85.300809 iter 60 value 84.802174 iter 70 value 82.737811 iter 80 value 81.287227 iter 90 value 80.404977 iter 100 value 79.992617 final value 79.992617 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 107.042319 iter 10 value 94.171184 iter 20 value 88.960512 iter 30 value 86.330402 iter 40 value 85.101070 iter 50 value 83.651489 iter 60 value 82.931026 iter 70 value 82.071525 iter 80 value 81.389718 iter 90 value 80.304252 iter 100 value 79.961520 final value 79.961520 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 103.547668 iter 10 value 94.054024 iter 20 value 92.312498 iter 30 value 87.758327 iter 40 value 85.292898 iter 50 value 82.911305 iter 60 value 82.285372 iter 70 value 79.640722 iter 80 value 79.536553 iter 90 value 79.496330 iter 100 value 79.465196 final value 79.465196 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 103.214212 iter 10 value 94.203343 iter 20 value 93.614447 iter 30 value 84.125505 iter 40 value 83.631873 iter 50 value 83.480372 iter 60 value 82.514753 iter 70 value 81.789490 iter 80 value 81.287605 iter 90 value 79.997962 iter 100 value 79.794571 final value 79.794571 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 116.066456 iter 10 value 93.910418 iter 20 value 93.272393 iter 30 value 88.495141 iter 40 value 85.099297 iter 50 value 83.508008 iter 60 value 80.733039 iter 70 value 80.405322 iter 80 value 80.266904 iter 90 value 79.593629 iter 100 value 79.373419 final value 79.373419 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 123.060310 iter 10 value 94.010793 iter 20 value 88.049162 iter 30 value 86.792499 iter 40 value 85.617079 iter 50 value 82.910391 iter 60 value 81.993627 iter 70 value 80.060948 iter 80 value 79.563817 iter 90 value 79.240359 iter 100 value 79.184021 final value 79.184021 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.068484 iter 10 value 94.054569 iter 20 value 94.003166 iter 30 value 90.714957 iter 40 value 90.006177 iter 50 value 90.004869 iter 60 value 90.004128 iter 70 value 90.003907 iter 80 value 90.003803 iter 90 value 90.003508 final value 90.003486 converged Fitting Repeat 2 # weights: 103 initial value 100.821896 final value 94.054658 converged Fitting Repeat 3 # weights: 103 initial value 95.762531 iter 10 value 94.054605 iter 20 value 94.052937 iter 30 value 83.279609 final value 83.184531 converged Fitting Repeat 4 # weights: 103 initial value 96.753065 final value 94.054425 converged Fitting Repeat 5 # weights: 103 initial value 101.997332 iter 10 value 94.054624 iter 20 value 94.052912 iter 30 value 91.829209 iter 40 value 86.276209 iter 50 value 86.266003 iter 60 value 86.264842 iter 70 value 86.263758 iter 80 value 86.260546 iter 90 value 86.022402 iter 100 value 85.996033 final value 85.996033 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 97.124137 iter 10 value 94.057422 iter 20 value 91.836325 iter 30 value 86.100167 iter 40 value 83.874222 iter 50 value 83.767531 iter 60 value 83.638704 iter 70 value 83.434941 iter 80 value 83.433102 iter 90 value 83.368273 iter 100 value 83.259732 final value 83.259732 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 98.781580 iter 10 value 93.920853 iter 20 value 93.916217 iter 30 value 93.493719 iter 40 value 88.182295 iter 50 value 85.246619 iter 60 value 83.722229 final value 83.702903 converged Fitting Repeat 3 # weights: 305 initial value 95.790470 iter 10 value 94.055989 iter 20 value 94.048863 iter 30 value 92.329899 final value 88.348486 converged Fitting Repeat 4 # weights: 305 initial value 100.609304 iter 10 value 94.010758 iter 20 value 90.280505 iter 30 value 90.099947 iter 40 value 90.099281 iter 50 value 88.071890 iter 60 value 88.036328 iter 70 value 87.469938 iter 80 value 86.914817 final value 86.777553 converged Fitting Repeat 5 # weights: 305 initial value 96.478344 iter 10 value 93.920218 iter 20 value 93.915843 iter 30 value 93.061886 iter 40 value 90.870391 iter 50 value 90.267055 iter 60 value 83.221158 iter 70 value 83.198300 iter 80 value 83.184094 final value 83.183783 converged Fitting Repeat 1 # weights: 507 initial value 95.355512 iter 10 value 93.520441 iter 20 value 93.514352 iter 30 value 93.493120 iter 40 value 93.491186 iter 50 value 84.934476 iter 60 value 84.229742 iter 70 value 84.200328 final value 84.200275 converged Fitting Repeat 2 # weights: 507 initial value 108.254512 iter 10 value 91.386696 iter 20 value 87.533722 iter 30 value 87.530864 iter 40 value 84.907723 iter 50 value 84.292614 iter 60 value 84.178313 iter 70 value 83.948352 iter 80 value 83.947666 iter 90 value 83.946448 final value 83.945398 converged Fitting Repeat 3 # weights: 507 initial value 95.795291 iter 10 value 93.636898 iter 20 value 93.526631 iter 30 value 91.021372 iter 40 value 87.130490 iter 50 value 84.611416 iter 60 value 84.156398 iter 70 value 84.103800 iter 80 value 84.103222 iter 90 value 84.005592 iter 100 value 83.709291 final value 83.709291 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 100.675257 iter 10 value 93.515876 iter 20 value 93.512695 iter 30 value 90.814741 iter 40 value 88.536809 iter 50 value 86.952262 iter 60 value 85.817933 iter 70 value 82.264922 iter 80 value 82.091641 iter 90 value 81.971584 iter 100 value 81.971353 final value 81.971353 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 111.866211 iter 10 value 94.060478 iter 20 value 94.026422 iter 30 value 89.845062 iter 40 value 89.723610 iter 50 value 89.723307 iter 60 value 89.723027 iter 70 value 89.721862 final value 89.721759 converged Fitting Repeat 1 # weights: 103 initial value 91.554604 iter 10 value 82.862777 iter 20 value 82.664644 iter 30 value 82.361271 iter 40 value 82.353330 final value 82.352776 converged Fitting Repeat 2 # weights: 103 initial value 101.376584 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 100.257267 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 96.506796 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 97.287205 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 96.176308 iter 10 value 89.842014 iter 20 value 89.835867 final value 89.835846 converged Fitting Repeat 2 # weights: 305 initial value 99.734889 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 109.718252 iter 10 value 94.112644 final value 94.112570 converged Fitting Repeat 4 # weights: 305 initial value 103.960001 final value 94.466823 converged Fitting Repeat 5 # weights: 305 initial value 115.566788 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 113.845802 iter 10 value 94.312970 iter 20 value 94.312045 final value 94.312039 converged Fitting Repeat 2 # weights: 507 initial value 95.732121 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 98.276152 final value 94.112570 converged Fitting Repeat 4 # weights: 507 initial value 101.034863 iter 10 value 93.075517 iter 20 value 92.922940 iter 30 value 92.293639 final value 92.293621 converged Fitting Repeat 5 # weights: 507 initial value 100.722396 final value 94.466823 converged Fitting Repeat 1 # weights: 103 initial value 106.383122 iter 10 value 94.492532 iter 20 value 88.985206 iter 30 value 85.670006 iter 40 value 85.071729 iter 50 value 84.535268 iter 60 value 84.434448 iter 70 value 84.324227 final value 84.324218 converged Fitting Repeat 2 # weights: 103 initial value 100.583400 iter 10 value 94.535079 iter 20 value 94.488207 iter 30 value 94.191285 iter 40 value 88.973446 iter 50 value 86.074817 iter 60 value 85.857336 iter 70 value 85.745340 iter 80 value 84.656642 iter 90 value 84.325851 iter 100 value 84.324220 final value 84.324220 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 103.317115 iter 10 value 94.491681 iter 20 value 93.133347 iter 30 value 92.968731 iter 40 value 92.950999 iter 50 value 92.539577 iter 60 value 90.647769 iter 70 value 86.286118 iter 80 value 85.272188 iter 90 value 84.691874 iter 100 value 84.283341 final value 84.283341 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 98.496356 iter 10 value 92.019900 iter 20 value 85.670918 iter 30 value 85.226550 iter 40 value 84.792826 iter 50 value 84.637544 iter 60 value 84.608997 iter 70 value 84.587176 final value 84.585599 converged Fitting Repeat 5 # weights: 103 initial value 98.616427 iter 10 value 94.443271 iter 20 value 93.960700 iter 30 value 88.290349 iter 40 value 86.040413 iter 50 value 85.327891 iter 60 value 84.752281 iter 70 value 84.750551 final value 84.750498 converged Fitting Repeat 1 # weights: 305 initial value 112.580647 iter 10 value 91.724174 iter 20 value 83.524731 iter 30 value 81.725829 iter 40 value 81.532362 iter 50 value 80.665212 iter 60 value 80.294497 iter 70 value 80.022146 iter 80 value 79.962323 iter 90 value 79.867424 iter 100 value 79.854812 final value 79.854812 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 110.667688 iter 10 value 94.542886 iter 20 value 92.742426 iter 30 value 91.158069 iter 40 value 90.795638 iter 50 value 83.551161 iter 60 value 83.043910 iter 70 value 82.080611 iter 80 value 80.761482 iter 90 value 80.590563 iter 100 value 80.529141 final value 80.529141 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 107.788132 iter 10 value 94.535163 iter 20 value 94.164320 iter 30 value 92.948714 iter 40 value 91.007209 iter 50 value 85.962822 iter 60 value 85.544204 iter 70 value 82.076115 iter 80 value 81.351779 iter 90 value 81.030915 iter 100 value 80.926555 final value 80.926555 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 103.733663 iter 10 value 93.921976 iter 20 value 89.430292 iter 30 value 86.546903 iter 40 value 85.263357 iter 50 value 84.283068 iter 60 value 84.044318 iter 70 value 83.490224 iter 80 value 81.323199 iter 90 value 80.370140 iter 100 value 80.232665 final value 80.232665 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.543035 iter 10 value 94.433561 iter 20 value 91.482993 iter 30 value 88.302389 iter 40 value 84.258343 iter 50 value 83.161585 iter 60 value 82.541999 iter 70 value 82.347883 iter 80 value 82.080196 iter 90 value 80.588597 iter 100 value 80.150073 final value 80.150073 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 124.485307 iter 10 value 94.533631 iter 20 value 92.544974 iter 30 value 87.902674 iter 40 value 87.073561 iter 50 value 86.784837 iter 60 value 86.732669 iter 70 value 85.713638 iter 80 value 84.239939 iter 90 value 83.111348 iter 100 value 81.548807 final value 81.548807 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 109.297561 iter 10 value 93.946323 iter 20 value 91.482524 iter 30 value 86.456385 iter 40 value 83.862429 iter 50 value 81.909837 iter 60 value 81.046414 iter 70 value 80.509470 iter 80 value 80.310130 iter 90 value 79.826442 iter 100 value 79.467713 final value 79.467713 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 105.599121 iter 10 value 93.861347 iter 20 value 89.672254 iter 30 value 85.906050 iter 40 value 83.679059 iter 50 value 82.345006 iter 60 value 81.240849 iter 70 value 80.194190 iter 80 value 80.079009 iter 90 value 80.058805 iter 100 value 79.981299 final value 79.981299 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 105.320514 iter 10 value 94.537963 iter 20 value 89.309350 iter 30 value 85.953100 iter 40 value 83.313743 iter 50 value 81.726527 iter 60 value 81.253200 iter 70 value 80.879331 iter 80 value 80.745571 iter 90 value 80.711618 iter 100 value 80.520641 final value 80.520641 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 130.559301 iter 10 value 94.417007 iter 20 value 87.123387 iter 30 value 84.669252 iter 40 value 83.120140 iter 50 value 82.083196 iter 60 value 81.542060 iter 70 value 79.959799 iter 80 value 79.694005 iter 90 value 79.582490 iter 100 value 79.513343 final value 79.513343 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 104.659160 iter 10 value 94.485169 final value 94.484215 converged Fitting Repeat 2 # weights: 103 initial value 114.806627 final value 94.468320 converged Fitting Repeat 3 # weights: 103 initial value 101.582367 final value 94.486074 converged Fitting Repeat 4 # weights: 103 initial value 102.927351 iter 10 value 94.468237 iter 20 value 94.467248 final value 94.467194 converged Fitting Repeat 5 # weights: 103 initial value 103.552438 final value 94.485952 converged Fitting Repeat 1 # weights: 305 initial value 99.514909 iter 10 value 94.488876 iter 20 value 94.480533 iter 30 value 84.858263 iter 40 value 84.823633 final value 84.823325 converged Fitting Repeat 2 # weights: 305 initial value 105.290405 iter 10 value 94.488736 iter 20 value 93.093533 iter 30 value 89.758895 iter 40 value 89.237552 iter 50 value 87.808327 iter 60 value 87.774163 iter 70 value 87.773904 iter 80 value 87.766580 iter 90 value 87.765855 iter 100 value 87.673683 final value 87.673683 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 101.392961 iter 10 value 94.488574 iter 20 value 89.460354 iter 30 value 86.310660 iter 40 value 86.310466 iter 50 value 86.303069 final value 86.302166 converged Fitting Repeat 4 # weights: 305 initial value 98.325384 iter 10 value 94.294865 iter 20 value 94.292856 iter 30 value 94.264544 iter 40 value 84.427256 iter 50 value 84.344345 iter 60 value 84.325944 iter 70 value 84.320283 iter 80 value 84.316198 iter 90 value 83.787528 final value 83.787478 converged Fitting Repeat 5 # weights: 305 initial value 99.798710 iter 10 value 94.489020 iter 20 value 94.484225 iter 30 value 88.079684 iter 40 value 84.822890 iter 50 value 84.781182 iter 60 value 84.777354 iter 70 value 84.776511 iter 80 value 84.775031 iter 90 value 83.864302 iter 100 value 83.751106 final value 83.751106 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 102.071667 iter 10 value 94.475540 iter 20 value 94.137860 final value 94.112912 converged Fitting Repeat 2 # weights: 507 initial value 114.044137 iter 10 value 94.085040 iter 20 value 94.082544 iter 30 value 94.070046 iter 40 value 94.060934 iter 50 value 92.940249 iter 60 value 87.299926 iter 70 value 83.825300 iter 80 value 83.787618 iter 90 value 83.787528 iter 100 value 83.780119 final value 83.780119 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 107.116246 iter 10 value 94.492017 iter 20 value 94.435898 final value 93.615365 converged Fitting Repeat 4 # weights: 507 initial value 112.506878 iter 10 value 94.048548 iter 20 value 89.958330 iter 30 value 89.846902 iter 40 value 82.793026 iter 50 value 82.782699 iter 60 value 82.748708 iter 70 value 82.745374 iter 80 value 82.615878 iter 90 value 82.578684 iter 100 value 82.575981 final value 82.575981 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 99.198335 iter 10 value 94.491903 iter 20 value 94.484230 final value 94.484221 converged Fitting Repeat 1 # weights: 103 initial value 96.156118 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 100.108976 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 97.372846 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 96.037946 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 102.880858 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 105.478323 final value 94.026542 converged Fitting Repeat 2 # weights: 305 initial value 97.467962 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 114.096099 iter 10 value 94.028858 iter 20 value 94.024564 iter 20 value 94.024564 iter 20 value 94.024564 final value 94.024564 converged Fitting Repeat 4 # weights: 305 initial value 110.308097 final value 94.484211 converged Fitting Repeat 5 # weights: 305 initial value 101.213486 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 94.622040 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 99.108895 final value 94.026541 converged Fitting Repeat 3 # weights: 507 initial value 109.795670 final value 94.026542 converged Fitting Repeat 4 # weights: 507 initial value 95.879247 iter 10 value 94.484211 iter 10 value 94.484211 iter 10 value 94.484211 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 99.638133 iter 10 value 94.026542 iter 10 value 94.026542 iter 10 value 94.026542 final value 94.026542 converged Fitting Repeat 1 # weights: 103 initial value 99.625738 iter 10 value 94.193771 iter 20 value 94.114028 iter 30 value 86.401300 iter 40 value 85.958430 iter 50 value 85.508131 iter 60 value 85.238711 iter 70 value 85.086525 iter 80 value 84.791622 iter 90 value 84.661529 iter 100 value 84.630818 final value 84.630818 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 98.285477 iter 10 value 89.121535 iter 20 value 87.255483 iter 30 value 86.902831 iter 40 value 84.524263 iter 50 value 83.906284 iter 60 value 83.880164 iter 70 value 83.632196 iter 80 value 83.555918 iter 90 value 83.470886 iter 100 value 83.462980 final value 83.462980 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 101.996718 iter 10 value 94.495764 iter 20 value 89.720105 iter 30 value 88.966008 iter 40 value 88.517315 iter 50 value 88.365528 iter 60 value 87.696230 iter 70 value 86.732996 iter 80 value 83.920114 iter 90 value 83.106759 iter 100 value 83.070430 final value 83.070430 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 97.625477 iter 10 value 94.480382 iter 20 value 94.290578 iter 30 value 94.130795 iter 40 value 94.124373 iter 50 value 89.288650 iter 60 value 88.207714 iter 70 value 88.101387 iter 80 value 88.096518 iter 90 value 88.075013 iter 100 value 87.740625 final value 87.740625 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 106.338592 iter 10 value 94.427099 iter 20 value 94.127189 iter 30 value 94.125364 iter 40 value 88.641180 iter 50 value 85.625000 iter 60 value 84.567354 iter 70 value 83.620254 iter 80 value 83.481072 iter 90 value 83.038058 iter 100 value 83.035321 final value 83.035321 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 105.396407 iter 10 value 91.251104 iter 20 value 86.115793 iter 30 value 85.598550 iter 40 value 83.988811 iter 50 value 83.522081 iter 60 value 83.459770 iter 70 value 83.211989 iter 80 value 83.079149 iter 90 value 83.034200 iter 100 value 82.851832 final value 82.851832 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 106.760591 iter 10 value 94.458907 iter 20 value 90.598490 iter 30 value 86.000081 iter 40 value 85.038677 iter 50 value 84.430188 iter 60 value 83.822125 iter 70 value 83.214310 iter 80 value 82.404894 iter 90 value 82.056694 iter 100 value 81.944761 final value 81.944761 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.579574 iter 10 value 94.632806 iter 20 value 91.216057 iter 30 value 85.545989 iter 40 value 83.596347 iter 50 value 82.900851 iter 60 value 82.465222 iter 70 value 82.335805 iter 80 value 81.935383 iter 90 value 81.907805 iter 100 value 81.866771 final value 81.866771 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 112.371405 iter 10 value 94.555580 iter 20 value 93.709699 iter 30 value 88.220226 iter 40 value 85.166114 iter 50 value 84.682893 iter 60 value 83.738486 iter 70 value 82.796009 iter 80 value 82.112428 iter 90 value 81.856016 iter 100 value 81.807198 final value 81.807198 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 105.548000 iter 10 value 94.502641 iter 20 value 90.332999 iter 30 value 89.004219 iter 40 value 88.718979 iter 50 value 86.901794 iter 60 value 86.147172 iter 70 value 85.461333 iter 80 value 84.573645 iter 90 value 83.870019 iter 100 value 83.049726 final value 83.049726 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 117.866991 iter 10 value 94.501676 iter 20 value 89.005967 iter 30 value 88.799707 iter 40 value 87.741472 iter 50 value 85.544191 iter 60 value 83.966732 iter 70 value 82.731640 iter 80 value 81.869302 iter 90 value 81.759371 iter 100 value 81.687276 final value 81.687276 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 108.931926 iter 10 value 96.714209 iter 20 value 88.798945 iter 30 value 86.925021 iter 40 value 86.421372 iter 50 value 84.846986 iter 60 value 82.990160 iter 70 value 82.310838 iter 80 value 82.190767 iter 90 value 82.037214 iter 100 value 81.933065 final value 81.933065 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.971644 iter 10 value 94.699613 iter 20 value 94.403064 iter 30 value 93.250644 iter 40 value 86.993377 iter 50 value 85.352239 iter 60 value 84.700236 iter 70 value 83.888898 iter 80 value 82.906699 iter 90 value 82.639204 iter 100 value 82.279044 final value 82.279044 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 107.022880 iter 10 value 94.236519 iter 20 value 87.861729 iter 30 value 86.883460 iter 40 value 86.576270 iter 50 value 85.349493 iter 60 value 83.970709 iter 70 value 83.174923 iter 80 value 82.537853 iter 90 value 81.968804 iter 100 value 81.610793 final value 81.610793 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 114.537426 iter 10 value 94.477041 iter 20 value 86.816004 iter 30 value 85.356552 iter 40 value 84.731126 iter 50 value 84.512348 iter 60 value 84.344834 iter 70 value 83.667479 iter 80 value 82.575209 iter 90 value 82.234816 iter 100 value 82.041920 final value 82.041920 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 97.676683 iter 10 value 94.486099 final value 94.484455 converged Fitting Repeat 2 # weights: 103 initial value 101.937450 final value 94.485742 converged Fitting Repeat 3 # weights: 103 initial value 100.173961 iter 10 value 94.028612 iter 20 value 94.027218 iter 30 value 94.019864 iter 40 value 86.060086 iter 50 value 85.959551 iter 60 value 85.955528 final value 85.955469 converged Fitting Repeat 4 # weights: 103 initial value 102.547793 final value 94.324463 converged Fitting Repeat 5 # weights: 103 initial value 100.393289 final value 94.485970 converged Fitting Repeat 1 # weights: 305 initial value 114.003538 iter 10 value 94.560438 iter 20 value 94.549156 iter 30 value 94.046390 iter 40 value 88.955804 iter 50 value 86.761283 iter 60 value 86.306398 iter 70 value 86.181247 iter 80 value 85.591017 iter 90 value 84.963373 iter 100 value 84.952157 final value 84.952157 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 95.740025 iter 10 value 94.489220 iter 20 value 94.378728 iter 30 value 85.484449 iter 40 value 85.414219 final value 85.414129 converged Fitting Repeat 3 # weights: 305 initial value 95.484392 iter 10 value 94.107943 iter 20 value 94.052486 final value 94.052127 converged Fitting Repeat 4 # weights: 305 initial value 103.332986 iter 10 value 94.488953 iter 20 value 94.484287 final value 94.026865 converged Fitting Repeat 5 # weights: 305 initial value 106.288004 iter 10 value 94.488795 iter 20 value 87.037124 iter 30 value 86.267505 iter 30 value 86.267504 iter 30 value 86.267504 final value 86.267504 converged Fitting Repeat 1 # weights: 507 initial value 104.779735 iter 10 value 94.035581 iter 20 value 94.027235 iter 30 value 92.676337 iter 40 value 92.622502 iter 50 value 92.601018 iter 60 value 92.534813 iter 70 value 89.193382 iter 80 value 86.586497 iter 90 value 86.384307 iter 100 value 86.363320 final value 86.363320 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 106.076672 iter 10 value 94.492280 iter 20 value 94.484262 iter 30 value 94.386978 iter 40 value 88.930140 iter 50 value 88.177387 iter 60 value 86.922710 iter 70 value 86.273620 iter 80 value 84.838405 iter 90 value 83.743162 iter 100 value 83.676048 final value 83.676048 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 107.235577 iter 10 value 92.813081 iter 20 value 92.737981 iter 30 value 92.239903 iter 40 value 92.002577 iter 50 value 91.994146 iter 60 value 91.933351 iter 70 value 91.731370 iter 80 value 91.730905 iter 90 value 91.730786 final value 91.730529 converged Fitting Repeat 4 # weights: 507 initial value 102.337133 iter 10 value 94.313971 iter 20 value 94.196494 iter 30 value 86.538180 iter 40 value 83.740499 iter 50 value 81.433969 iter 60 value 80.721428 iter 70 value 80.203914 iter 80 value 80.179575 iter 90 value 80.174883 iter 100 value 80.158835 final value 80.158835 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 101.584623 iter 10 value 94.150608 iter 20 value 94.052636 iter 30 value 93.095100 iter 40 value 93.093621 iter 50 value 93.088867 iter 60 value 93.088703 iter 70 value 93.087922 iter 80 value 92.247397 iter 90 value 92.094779 iter 100 value 92.027215 final value 92.027215 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.128809 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 110.289311 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 104.479561 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 102.966346 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 96.155793 iter 10 value 86.158330 iter 20 value 85.335970 iter 30 value 83.845035 iter 40 value 83.517895 final value 83.517788 converged Fitting Repeat 1 # weights: 305 initial value 96.672131 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 96.314587 iter 10 value 94.325113 iter 20 value 94.320332 final value 94.320310 converged Fitting Repeat 3 # weights: 305 initial value 106.728041 final value 94.484211 converged Fitting Repeat 4 # weights: 305 initial value 104.057913 iter 10 value 94.231734 final value 94.231729 converged Fitting Repeat 5 # weights: 305 initial value 99.369598 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 109.075382 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 125.486537 iter 10 value 94.484211 iter 10 value 94.484211 iter 10 value 94.484211 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 117.362256 iter 10 value 94.484211 iter 10 value 94.484211 iter 10 value 94.484211 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 104.779444 iter 10 value 94.231743 final value 94.231729 converged Fitting Repeat 5 # weights: 507 initial value 98.389508 final value 94.231729 converged Fitting Repeat 1 # weights: 103 initial value 97.617245 iter 10 value 94.320392 iter 20 value 93.510246 iter 30 value 88.342853 iter 40 value 83.831680 iter 50 value 83.149410 iter 60 value 82.593627 iter 70 value 82.362900 iter 80 value 81.606414 iter 90 value 81.512491 iter 100 value 81.371333 final value 81.371333 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 108.840548 iter 10 value 94.429728 iter 20 value 86.848456 iter 30 value 86.191953 iter 40 value 84.460332 iter 50 value 83.763268 iter 60 value 83.460891 iter 70 value 83.202621 iter 80 value 83.165382 iter 90 value 83.141757 final value 83.141521 converged Fitting Repeat 3 # weights: 103 initial value 96.555056 iter 10 value 94.230720 iter 20 value 86.983424 iter 30 value 85.037022 iter 40 value 83.989060 iter 50 value 83.955454 iter 60 value 82.840447 iter 70 value 82.107886 iter 80 value 81.594704 iter 90 value 81.280467 final value 81.280129 converged Fitting Repeat 4 # weights: 103 initial value 102.977087 iter 10 value 94.489788 iter 20 value 93.989741 iter 30 value 93.831132 iter 40 value 93.764025 iter 50 value 90.414832 iter 60 value 88.314594 iter 70 value 87.368574 iter 80 value 86.596368 iter 90 value 83.182395 iter 100 value 82.581953 final value 82.581953 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 96.638241 iter 10 value 94.483008 iter 20 value 93.713181 iter 30 value 89.259092 iter 40 value 85.702573 iter 50 value 84.537762 iter 60 value 84.260304 iter 70 value 84.251619 final value 84.251564 converged Fitting Repeat 1 # weights: 305 initial value 103.632920 iter 10 value 94.469692 iter 20 value 88.842327 iter 30 value 86.001790 iter 40 value 84.569667 iter 50 value 82.955102 iter 60 value 82.680550 iter 70 value 82.213379 iter 80 value 81.818684 iter 90 value 81.781548 iter 100 value 81.742708 final value 81.742708 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 115.928063 iter 10 value 94.390179 iter 20 value 91.829873 iter 30 value 88.219676 iter 40 value 86.382288 iter 50 value 84.841786 iter 60 value 82.005702 iter 70 value 81.249006 iter 80 value 80.696049 iter 90 value 79.960088 iter 100 value 79.797014 final value 79.797014 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 129.779512 iter 10 value 94.991226 iter 20 value 89.202280 iter 30 value 86.021535 iter 40 value 84.870494 iter 50 value 83.949479 iter 60 value 82.487582 iter 70 value 81.478450 iter 80 value 80.551006 iter 90 value 80.152532 iter 100 value 79.914335 final value 79.914335 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.225093 iter 10 value 94.477880 iter 20 value 92.884806 iter 30 value 89.146863 iter 40 value 86.056519 iter 50 value 85.115012 iter 60 value 84.565503 iter 70 value 84.356806 iter 80 value 83.260272 iter 90 value 81.227150 iter 100 value 80.642770 final value 80.642770 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 101.798733 iter 10 value 94.647050 iter 20 value 87.576003 iter 30 value 86.326429 iter 40 value 85.890185 iter 50 value 84.756703 iter 60 value 82.370433 iter 70 value 81.287202 iter 80 value 81.050672 iter 90 value 80.555712 iter 100 value 80.328223 final value 80.328223 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 112.855222 iter 10 value 94.392537 iter 20 value 93.923418 iter 30 value 93.749365 iter 40 value 88.296746 iter 50 value 86.979680 iter 60 value 85.730360 iter 70 value 83.430768 iter 80 value 81.927068 iter 90 value 81.645931 iter 100 value 81.082645 final value 81.082645 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 103.132584 iter 10 value 94.200114 iter 20 value 90.272124 iter 30 value 84.483927 iter 40 value 83.013840 iter 50 value 82.413430 iter 60 value 81.970269 iter 70 value 80.180145 iter 80 value 79.586361 iter 90 value 79.400109 iter 100 value 79.277979 final value 79.277979 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 114.225659 iter 10 value 94.460697 iter 20 value 88.283852 iter 30 value 85.467295 iter 40 value 80.853110 iter 50 value 80.390267 iter 60 value 80.245188 iter 70 value 79.790051 iter 80 value 79.618585 iter 90 value 79.542234 iter 100 value 79.512675 final value 79.512675 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 107.823433 iter 10 value 94.955825 iter 20 value 93.615216 iter 30 value 89.652312 iter 40 value 85.848512 iter 50 value 84.755132 iter 60 value 83.575567 iter 70 value 82.368302 iter 80 value 81.661229 iter 90 value 80.910273 iter 100 value 80.490729 final value 80.490729 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 110.989721 iter 10 value 94.894796 iter 20 value 94.356903 iter 30 value 88.903738 iter 40 value 87.206203 iter 50 value 86.559170 iter 60 value 84.586646 iter 70 value 82.031933 iter 80 value 80.833293 iter 90 value 80.068704 iter 100 value 79.848729 final value 79.848729 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 99.216289 final value 94.485646 converged Fitting Repeat 2 # weights: 103 initial value 101.641725 final value 94.485827 converged Fitting Repeat 3 # weights: 103 initial value 100.447269 final value 94.485879 converged Fitting Repeat 4 # weights: 103 initial value 99.470415 iter 10 value 94.485790 iter 20 value 94.484250 final value 94.484207 converged Fitting Repeat 5 # weights: 103 initial value 95.048038 final value 94.486040 converged Fitting Repeat 1 # weights: 305 initial value 102.419839 iter 10 value 93.706792 iter 20 value 88.872463 iter 30 value 85.765924 iter 40 value 85.449685 iter 50 value 85.170598 iter 60 value 85.169209 final value 85.167579 converged Fitting Repeat 2 # weights: 305 initial value 100.808942 iter 10 value 94.350291 iter 20 value 94.170290 iter 30 value 94.167441 iter 40 value 93.329080 iter 50 value 87.267626 iter 60 value 87.262170 iter 70 value 87.260611 iter 80 value 87.260341 iter 90 value 86.658410 final value 86.642550 converged Fitting Repeat 3 # weights: 305 initial value 103.204525 iter 10 value 94.489223 iter 20 value 94.427732 iter 30 value 85.138555 final value 83.757146 converged Fitting Repeat 4 # weights: 305 initial value 95.411846 iter 10 value 94.489149 iter 20 value 93.761067 iter 30 value 86.148329 iter 40 value 84.978199 iter 50 value 84.549296 iter 60 value 84.540684 iter 70 value 84.331213 iter 80 value 81.769199 iter 90 value 81.562256 iter 100 value 80.892754 final value 80.892754 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 105.872235 iter 10 value 94.491614 iter 20 value 94.392736 iter 30 value 86.801734 iter 40 value 85.448156 iter 50 value 85.438634 iter 60 value 85.114712 iter 70 value 84.894205 iter 80 value 84.877794 iter 90 value 83.190314 iter 100 value 82.872133 final value 82.872133 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 112.691363 iter 10 value 94.088679 iter 20 value 94.084223 iter 30 value 94.079996 iter 40 value 94.041821 iter 50 value 89.450561 iter 60 value 84.119957 iter 70 value 81.890062 iter 80 value 80.656353 iter 90 value 80.653962 final value 80.653743 converged Fitting Repeat 2 # weights: 507 initial value 102.229815 iter 10 value 94.469954 iter 20 value 94.339523 iter 30 value 94.165537 final value 94.165387 converged Fitting Repeat 3 # weights: 507 initial value 102.922421 iter 10 value 93.748151 iter 20 value 93.422444 iter 30 value 93.282379 iter 40 value 93.278626 iter 50 value 91.012889 iter 60 value 89.008642 iter 70 value 83.882321 iter 80 value 81.452509 iter 90 value 78.577036 iter 100 value 78.461193 final value 78.461193 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 97.790019 iter 10 value 94.491690 iter 20 value 94.217477 iter 30 value 93.702089 final value 93.702088 converged Fitting Repeat 5 # weights: 507 initial value 100.687212 iter 10 value 93.597197 iter 20 value 90.308769 iter 30 value 89.753516 iter 40 value 87.781363 iter 50 value 85.664354 iter 60 value 83.161815 iter 70 value 82.375168 iter 80 value 81.895043 iter 90 value 81.888435 iter 100 value 81.602481 final value 81.602481 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 134.329432 iter 10 value 114.889102 iter 20 value 108.490839 iter 30 value 107.287220 iter 40 value 104.957062 iter 50 value 102.253650 iter 60 value 101.208572 iter 70 value 101.029264 iter 80 value 100.967618 iter 90 value 100.941771 iter 100 value 100.901450 final value 100.901450 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 121.738788 iter 10 value 110.840517 iter 20 value 107.829658 iter 30 value 106.441542 iter 40 value 105.526140 iter 50 value 105.331010 iter 60 value 105.261857 iter 70 value 105.234064 iter 80 value 105.099841 iter 90 value 105.011568 iter 100 value 104.926478 final value 104.926478 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 140.338676 iter 10 value 118.135007 iter 20 value 117.749199 iter 30 value 116.661077 iter 40 value 109.182952 iter 50 value 107.805864 iter 60 value 107.523264 iter 70 value 106.368623 iter 80 value 106.010968 iter 90 value 105.485612 iter 100 value 103.571110 final value 103.571110 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 139.801192 iter 10 value 114.894511 iter 20 value 108.793600 iter 30 value 105.828994 iter 40 value 105.117628 iter 50 value 105.001761 iter 60 value 103.156279 iter 70 value 102.728909 iter 80 value 102.458624 iter 90 value 102.025379 final value 102.024334 converged Fitting Repeat 5 # weights: 305 initial value 128.712813 iter 10 value 117.879278 iter 20 value 115.998279 iter 30 value 107.474843 iter 40 value 106.894498 iter 50 value 104.875022 iter 60 value 103.741693 iter 70 value 102.928491 iter 80 value 102.822156 iter 90 value 102.767221 iter 100 value 102.695839 final value 102.695839 stopped after 100 iterations svmRadial ranger Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls < cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases Setting levels: control = Positive, case = Negative Setting direction: controls > cases RUNIT TEST PROTOCOL -- Mon Jun 24 22:50:49 2024 *********************************************** 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 47.721 1.198 49.885
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 52.348 | 1.959 | 54.420 | |
FreqInteractors | 0.267 | 0.016 | 0.283 | |
calculateAAC | 0.043 | 0.007 | 0.049 | |
calculateAutocor | 0.400 | 0.059 | 0.460 | |
calculateCTDC | 0.085 | 0.006 | 0.091 | |
calculateCTDD | 0.569 | 0.029 | 0.598 | |
calculateCTDT | 0.251 | 0.011 | 0.262 | |
calculateCTriad | 0.735 | 0.035 | 0.768 | |
calculateDC | 0.100 | 0.013 | 0.112 | |
calculateF | 0.306 | 0.022 | 0.329 | |
calculateKSAAP | 0.095 | 0.010 | 0.106 | |
calculateQD_Sm | 1.755 | 0.168 | 1.924 | |
calculateTC | 1.668 | 0.158 | 1.828 | |
calculateTC_Sm | 0.368 | 0.032 | 0.400 | |
corr_plot | 51.733 | 2.133 | 53.981 | |
enrichfindP | 0.462 | 0.073 | 7.870 | |
enrichfind_hp | 0.071 | 0.019 | 0.690 | |
enrichplot | 0.385 | 0.009 | 0.397 | |
filter_missing_values | 0.002 | 0.000 | 0.002 | |
getFASTA | 0.089 | 0.015 | 0.924 | |
getHPI | 0.000 | 0.000 | 0.001 | |
get_negativePPI | 0.001 | 0.000 | 0.002 | |
get_positivePPI | 0.000 | 0.001 | 0.000 | |
impute_missing_data | 0.001 | 0.000 | 0.002 | |
plotPPI | 0.075 | 0.003 | 0.079 | |
pred_ensembel | 16.028 | 0.320 | 13.575 | |
var_imp | 55.465 | 1.999 | 57.512 | |