Back to Multiple platform build/check report for BioC 3.19: simplified long |
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This page was generated on 2024-05-04 11:37:55 -0400 (Sat, 04 May 2024).
Hostname | OS | Arch (*) | R version | Installed pkgs |
---|---|---|---|---|
nebbiolo1 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4753 |
palomino3 | Windows Server 2022 Datacenter | x64 | 4.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" | 4486 |
lconway | macOS 12.7.1 Monterey | x86_64 | 4.4.0 beta (2024-04-14 r86421) -- "Puppy Cup" | 4519 |
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) | aarch64 | 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" | 4479 |
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 | ![]() | ||||||||
lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | ![]() | ||||||||
kunpeng2 | Linux (openEuler 22.03 LTS-SP1) / aarch64 | OK | OK | OK | ||||||||||
kjohnson3 | macOS 13.6.5 Ventura / arm64 | see weekly results here | ||||||||||||
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: F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz |
StartedAt: 2024-05-04 04:25:57 -0400 (Sat, 04 May 2024) |
EndedAt: 2024-05-04 04:30:44 -0400 (Sat, 04 May 2024) |
EllapsedTime: 287.0 seconds |
RetCode: 0 |
Status: OK |
CheckDir: HPiP.Rcheck |
Warnings: 0 |
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz ### ############################################################################## ############################################################################## * using log directory 'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck' * using R version 4.4.0 beta (2024-04-15 r86425 ucrt) * using platform: x86_64-w64-mingw32 * R was compiled by gcc.exe (GCC) 13.2.0 GNU Fortran (GCC) 13.2.0 * running under: Windows Server 2022 x64 (build 20348) * 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 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 FSmethod 32.00 2.14 34.22 var_imp 31.13 1.30 32.44 corr_plot 29.71 2.03 31.73 pred_ensembel 14.25 0.64 10.69 enrichfindP 0.58 0.22 17.82 * 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 'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log' for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.19-bioc/R/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 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > BiocGenerics:::testPackage('HPiP') No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE No results to show Please make sure that the organism is correct or set significant = FALSE avNNet Loading required package: ggplot2 Loading required package: lattice Fitting Repeat 1 # weights: 103 initial value 98.366514 iter 10 value 93.818713 iter 10 value 93.818713 iter 10 value 93.818713 final value 93.818713 converged Fitting Repeat 2 # weights: 103 initial value 101.376345 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 98.196576 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 96.203416 final value 94.052910 converged Fitting Repeat 5 # weights: 103 initial value 98.441032 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 99.582149 final value 93.981595 converged Fitting Repeat 2 # weights: 305 initial value 105.558016 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 107.973849 final value 94.052910 converged Fitting Repeat 4 # weights: 305 initial value 100.884093 final value 94.052910 converged Fitting Repeat 5 # weights: 305 initial value 99.976180 final value 94.052910 converged Fitting Repeat 1 # weights: 507 initial value 101.180758 iter 10 value 92.620299 iter 20 value 86.067321 iter 30 value 86.063420 final value 86.063406 converged Fitting Repeat 2 # weights: 507 initial value 98.096441 iter 10 value 93.875448 final value 93.875386 converged Fitting Repeat 3 # weights: 507 initial value 94.970950 final value 94.032967 converged Fitting Repeat 4 # weights: 507 initial value 118.092257 final value 94.052910 converged Fitting Repeat 5 # weights: 507 initial value 105.512387 iter 10 value 93.327756 final value 93.326351 converged Fitting Repeat 1 # weights: 103 initial value 97.830042 iter 10 value 94.048037 iter 20 value 87.151073 iter 30 value 86.234764 iter 40 value 86.087252 iter 50 value 85.432824 iter 60 value 82.583957 iter 70 value 82.250856 iter 80 value 82.225427 iter 90 value 82.216231 iter 100 value 82.215821 final value 82.215821 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 104.152036 iter 10 value 94.517721 iter 20 value 87.154170 iter 30 value 86.034636 iter 40 value 82.334457 iter 50 value 82.229245 iter 60 value 82.203298 final value 82.202797 converged Fitting Repeat 3 # weights: 103 initial value 103.597795 iter 10 value 90.869845 iter 20 value 84.531855 iter 30 value 84.123367 iter 40 value 84.095307 iter 50 value 82.650802 iter 60 value 82.543299 iter 70 value 82.375059 iter 80 value 82.206547 iter 90 value 82.202802 final value 82.202797 converged Fitting Repeat 4 # weights: 103 initial value 99.350962 iter 10 value 94.078662 iter 20 value 93.153943 iter 30 value 92.967677 iter 40 value 92.967125 iter 50 value 92.963325 iter 60 value 89.192272 iter 70 value 87.704197 iter 80 value 87.437069 iter 90 value 82.018448 iter 100 value 81.783389 final value 81.783389 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 106.492956 final value 94.056700 converged Fitting Repeat 1 # weights: 305 initial value 110.693768 iter 10 value 94.272071 iter 20 value 88.585085 iter 30 value 83.241556 iter 40 value 82.192204 iter 50 value 81.966079 iter 60 value 81.879717 iter 70 value 81.547346 iter 80 value 79.151240 iter 90 value 78.720759 iter 100 value 78.323093 final value 78.323093 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 102.248385 iter 10 value 89.677932 iter 20 value 82.102382 iter 30 value 81.866059 iter 40 value 81.325994 iter 50 value 81.206612 iter 60 value 81.173895 iter 70 value 81.162256 iter 80 value 80.705372 iter 90 value 79.326409 iter 100 value 78.737710 final value 78.737710 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 105.669665 iter 10 value 93.850278 iter 20 value 91.009006 iter 30 value 83.778543 iter 40 value 82.071332 iter 50 value 81.811851 iter 60 value 81.364032 iter 70 value 80.749995 iter 80 value 79.260622 iter 90 value 79.016988 iter 100 value 78.895914 final value 78.895914 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 108.953818 iter 10 value 94.050323 iter 20 value 93.010693 iter 30 value 89.799810 iter 40 value 85.450154 iter 50 value 82.988553 iter 60 value 81.578146 iter 70 value 80.976120 iter 80 value 79.758779 iter 90 value 79.316261 iter 100 value 78.845967 final value 78.845967 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 134.745878 iter 10 value 94.437211 iter 20 value 93.583806 iter 30 value 93.345073 iter 40 value 84.737470 iter 50 value 82.766840 iter 60 value 79.909919 iter 70 value 79.135013 iter 80 value 78.931066 iter 90 value 78.597436 iter 100 value 77.820239 final value 77.820239 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 110.230666 iter 10 value 94.010637 iter 20 value 84.956782 iter 30 value 82.471756 iter 40 value 82.049092 iter 50 value 81.887589 iter 60 value 81.481095 iter 70 value 79.183016 iter 80 value 78.011707 iter 90 value 77.945860 iter 100 value 77.815606 final value 77.815606 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 124.553384 iter 10 value 98.770527 iter 20 value 92.875742 iter 30 value 84.819217 iter 40 value 81.827006 iter 50 value 80.837752 iter 60 value 79.132630 iter 70 value 78.945422 iter 80 value 78.693331 iter 90 value 78.652644 iter 100 value 78.326026 final value 78.326026 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 119.715117 iter 10 value 88.437917 iter 20 value 82.759443 iter 30 value 81.998484 iter 40 value 81.482492 iter 50 value 79.478579 iter 60 value 79.128274 iter 70 value 79.023904 iter 80 value 78.641993 iter 90 value 78.519964 iter 100 value 78.409116 final value 78.409116 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 122.327891 iter 10 value 94.107283 iter 20 value 93.442078 iter 30 value 93.292416 iter 40 value 83.712255 iter 50 value 79.310225 iter 60 value 79.025858 iter 70 value 78.629890 iter 80 value 78.207180 iter 90 value 77.522095 iter 100 value 77.097891 final value 77.097891 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 122.693448 iter 10 value 94.864001 iter 20 value 85.311202 iter 30 value 83.729322 iter 40 value 80.402978 iter 50 value 79.443984 iter 60 value 78.748607 iter 70 value 77.723123 iter 80 value 77.306562 iter 90 value 77.224377 iter 100 value 77.207837 final value 77.207837 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 96.640121 iter 10 value 93.822099 iter 20 value 93.811704 iter 30 value 93.811439 iter 40 value 93.810353 final value 93.810312 converged Fitting Repeat 2 # weights: 103 initial value 95.478353 final value 94.054442 converged Fitting Repeat 3 # weights: 103 initial value 95.741223 final value 94.054562 converged Fitting Repeat 4 # weights: 103 initial value 99.382321 final value 94.054383 converged Fitting Repeat 5 # weights: 103 initial value 94.169216 final value 94.054741 converged Fitting Repeat 1 # weights: 305 initial value 96.362929 iter 10 value 92.775667 iter 20 value 92.689641 iter 30 value 92.506277 iter 40 value 92.505007 iter 50 value 92.503773 iter 60 value 92.502422 final value 92.502413 converged Fitting Repeat 2 # weights: 305 initial value 105.695398 iter 10 value 94.059588 iter 20 value 93.957980 iter 30 value 93.332429 iter 40 value 93.195141 iter 50 value 93.189855 iter 60 value 84.843901 final value 84.840730 converged Fitting Repeat 3 # weights: 305 initial value 105.168974 iter 10 value 94.037952 iter 20 value 94.033089 iter 30 value 93.544222 iter 40 value 92.381310 iter 50 value 85.370229 iter 60 value 78.271963 iter 70 value 78.168882 iter 80 value 78.142191 final value 78.142156 converged Fitting Repeat 4 # weights: 305 initial value 112.067821 iter 10 value 93.609170 iter 20 value 93.350735 iter 30 value 86.858086 iter 40 value 81.920588 iter 50 value 78.864228 iter 60 value 77.419517 iter 70 value 77.380052 final value 77.379902 converged Fitting Repeat 5 # weights: 305 initial value 113.851989 iter 10 value 94.039810 iter 20 value 93.989493 iter 30 value 81.172930 iter 40 value 81.148426 iter 50 value 81.142005 final value 81.141956 converged Fitting Repeat 1 # weights: 507 initial value 103.979376 iter 10 value 94.064047 iter 20 value 93.444495 iter 30 value 88.036168 iter 40 value 86.721549 iter 50 value 84.751727 iter 60 value 83.514238 iter 70 value 78.167363 iter 80 value 78.077271 final value 78.072126 converged Fitting Repeat 2 # weights: 507 initial value 97.970221 iter 10 value 92.276174 iter 20 value 91.262288 iter 30 value 91.256807 iter 40 value 90.579521 iter 50 value 82.830023 iter 60 value 80.988018 iter 70 value 80.749205 final value 80.748933 converged Fitting Repeat 3 # weights: 507 initial value 95.044637 iter 10 value 94.055664 iter 20 value 84.181582 iter 30 value 83.246715 iter 40 value 83.242867 iter 50 value 81.194682 iter 60 value 80.209908 iter 70 value 78.982704 iter 80 value 77.791982 iter 90 value 77.782122 final value 77.781678 converged Fitting Repeat 4 # weights: 507 initial value 110.913902 iter 10 value 94.061558 iter 20 value 94.045731 iter 30 value 83.675101 iter 40 value 81.086404 iter 50 value 78.215138 iter 60 value 76.914323 iter 70 value 76.510499 iter 80 value 76.506708 iter 90 value 76.505835 iter 100 value 76.504303 final value 76.504303 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 98.014785 iter 10 value 93.827208 iter 20 value 91.501631 iter 30 value 81.186116 iter 40 value 81.013872 iter 50 value 80.973313 iter 60 value 80.969763 final value 80.969412 converged Fitting Repeat 1 # weights: 103 initial value 95.386069 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 111.113370 final value 94.354396 converged Fitting Repeat 3 # weights: 103 initial value 108.592763 final value 94.354396 converged Fitting Repeat 4 # weights: 103 initial value 94.491805 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 95.042009 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 108.214273 final value 94.354396 converged Fitting Repeat 2 # weights: 305 initial value 97.641361 iter 10 value 93.621336 final value 93.621189 converged Fitting Repeat 3 # weights: 305 initial value 98.921943 iter 10 value 92.210983 final value 92.186364 converged Fitting Repeat 4 # weights: 305 initial value 101.815943 iter 10 value 94.307939 final value 94.046703 converged Fitting Repeat 5 # weights: 305 initial value 100.362996 final value 94.289216 converged Fitting Repeat 1 # weights: 507 initial value 118.480949 final value 94.484211 converged Fitting Repeat 2 # weights: 507 initial value 99.210784 final value 94.484211 converged Fitting Repeat 3 # weights: 507 initial value 106.648114 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 106.969356 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 105.055721 final value 94.354396 converged Fitting Repeat 1 # weights: 103 initial value 111.344329 iter 10 value 94.473259 iter 20 value 92.374413 iter 30 value 91.613332 iter 40 value 91.578654 iter 50 value 88.145556 iter 60 value 84.620447 iter 70 value 84.320856 iter 80 value 84.165312 iter 90 value 82.861721 iter 100 value 82.361085 final value 82.361085 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 108.077999 iter 10 value 94.374970 iter 20 value 88.885102 iter 30 value 88.292891 iter 40 value 87.550407 iter 50 value 87.297401 iter 60 value 86.056427 iter 70 value 85.905876 iter 70 value 85.905876 final value 85.905876 converged Fitting Repeat 3 # weights: 103 initial value 100.127934 iter 10 value 94.485589 iter 20 value 88.632970 iter 30 value 87.368710 iter 40 value 85.309185 iter 50 value 83.229412 iter 60 value 82.887583 iter 70 value 82.447479 iter 80 value 82.373278 iter 90 value 82.304934 iter 100 value 82.291542 final value 82.291542 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 102.225878 iter 10 value 94.489717 iter 20 value 94.486612 iter 30 value 94.295777 iter 40 value 93.832478 iter 50 value 93.654370 iter 60 value 91.611627 iter 70 value 84.813253 iter 80 value 83.778416 iter 90 value 83.552190 iter 100 value 83.494310 final value 83.494310 stopped after 100 iterations Fitting Repeat 5 # weights: 103 initial value 98.789788 iter 10 value 94.487935 iter 20 value 94.395263 iter 30 value 94.382825 iter 40 value 94.373485 iter 50 value 93.868776 iter 60 value 89.485288 iter 70 value 85.757711 iter 80 value 83.965887 iter 90 value 83.258271 iter 100 value 83.054893 final value 83.054893 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 106.608581 iter 10 value 94.352245 iter 20 value 89.099021 iter 30 value 86.829524 iter 40 value 85.332457 iter 50 value 82.736003 iter 60 value 81.865432 iter 70 value 81.452370 iter 80 value 81.374832 iter 90 value 81.339167 iter 100 value 81.277031 final value 81.277031 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 105.706230 iter 10 value 94.508880 iter 20 value 93.006301 iter 30 value 89.036989 iter 40 value 88.421870 iter 50 value 85.192980 iter 60 value 84.072073 iter 70 value 83.761165 iter 80 value 83.478742 iter 90 value 83.035975 iter 100 value 82.296568 final value 82.296568 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 113.342820 iter 10 value 94.978139 iter 20 value 93.997360 iter 30 value 93.911133 iter 40 value 93.814516 iter 50 value 90.666463 iter 60 value 87.178542 iter 70 value 85.605116 iter 80 value 82.923688 iter 90 value 81.813583 iter 100 value 81.723667 final value 81.723667 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 103.123922 iter 10 value 94.188341 iter 20 value 88.260928 iter 30 value 87.679126 iter 40 value 87.434954 iter 50 value 87.071320 iter 60 value 85.934465 iter 70 value 85.643202 iter 80 value 85.236155 iter 90 value 83.493994 iter 100 value 82.931289 final value 82.931289 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 107.034565 iter 10 value 94.450983 iter 20 value 87.070312 iter 30 value 86.194552 iter 40 value 85.930255 iter 50 value 85.853143 iter 60 value 84.756648 iter 70 value 83.941861 iter 80 value 83.664261 iter 90 value 83.512195 iter 100 value 83.482277 final value 83.482277 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 110.211527 iter 10 value 94.401648 iter 20 value 89.771682 iter 30 value 84.842448 iter 40 value 84.186548 iter 50 value 83.459174 iter 60 value 82.504522 iter 70 value 81.436229 iter 80 value 80.955818 iter 90 value 80.828751 iter 100 value 80.686718 final value 80.686718 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 105.873505 iter 10 value 94.478640 iter 20 value 89.497601 iter 30 value 86.506310 iter 40 value 85.777074 iter 50 value 84.944726 iter 60 value 84.022710 iter 70 value 82.615600 iter 80 value 81.380522 iter 90 value 81.050716 iter 100 value 80.909714 final value 80.909714 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 108.130110 iter 10 value 94.252314 iter 20 value 87.780167 iter 30 value 87.212189 iter 40 value 87.113872 iter 50 value 84.413818 iter 60 value 83.171987 iter 70 value 82.660913 iter 80 value 81.973513 iter 90 value 81.484703 iter 100 value 81.221795 final value 81.221795 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 123.178815 iter 10 value 94.408925 iter 20 value 86.919190 iter 30 value 84.057652 iter 40 value 82.704310 iter 50 value 82.255716 iter 60 value 81.755997 iter 70 value 81.692803 iter 80 value 81.481303 iter 90 value 81.345024 iter 100 value 81.291927 final value 81.291927 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 104.199328 iter 10 value 95.350987 iter 20 value 92.573120 iter 30 value 88.261355 iter 40 value 84.655676 iter 50 value 83.366256 iter 60 value 82.136233 iter 70 value 81.909459 iter 80 value 81.876162 iter 90 value 81.842645 iter 100 value 81.688276 final value 81.688276 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 105.045907 final value 94.485931 converged Fitting Repeat 2 # weights: 103 initial value 107.291523 final value 94.485998 converged Fitting Repeat 3 # weights: 103 initial value 99.776308 final value 94.485552 converged Fitting Repeat 4 # weights: 103 initial value 106.337185 iter 10 value 91.184934 iter 20 value 91.155044 iter 30 value 91.154228 iter 40 value 91.153129 iter 50 value 91.152999 iter 60 value 91.120799 iter 70 value 91.110249 final value 91.110168 converged Fitting Repeat 5 # weights: 103 initial value 95.719912 final value 94.485838 converged Fitting Repeat 1 # weights: 305 initial value 98.473814 iter 10 value 94.488790 iter 20 value 93.725452 iter 30 value 91.791359 iter 40 value 91.407691 iter 50 value 91.103460 iter 60 value 91.074094 iter 70 value 91.073587 final value 91.073582 converged Fitting Repeat 2 # weights: 305 initial value 107.553326 iter 10 value 94.388463 iter 20 value 92.492856 iter 30 value 92.216693 iter 40 value 87.038404 iter 50 value 86.812976 iter 60 value 86.796356 iter 70 value 86.791542 iter 70 value 86.791541 final value 86.791541 converged Fitting Repeat 3 # weights: 305 initial value 96.420933 iter 10 value 94.488599 iter 20 value 94.475254 iter 30 value 93.812791 iter 40 value 91.456615 iter 50 value 86.403604 iter 60 value 86.106899 iter 70 value 86.105282 iter 80 value 86.102816 final value 86.102246 converged Fitting Repeat 4 # weights: 305 initial value 114.454169 iter 10 value 94.489252 iter 20 value 94.484309 iter 30 value 92.113185 iter 40 value 89.842741 iter 50 value 86.434402 iter 60 value 86.407333 iter 70 value 86.270517 iter 80 value 86.268523 iter 90 value 86.267551 iter 100 value 86.230386 final value 86.230386 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 95.056184 iter 10 value 94.359463 iter 20 value 93.865065 iter 30 value 93.724364 iter 40 value 93.724207 final value 93.723786 converged Fitting Repeat 1 # weights: 507 initial value 96.839490 iter 10 value 94.491277 iter 20 value 94.446539 iter 30 value 91.846439 iter 40 value 91.821608 iter 50 value 91.816107 iter 60 value 91.549554 iter 70 value 87.534269 iter 80 value 87.409157 iter 90 value 87.024629 iter 100 value 86.658780 final value 86.658780 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 112.187021 iter 10 value 93.879847 iter 20 value 93.872047 iter 30 value 93.660926 final value 93.535991 converged Fitting Repeat 3 # weights: 507 initial value 115.029087 iter 10 value 94.489417 iter 20 value 94.442115 iter 30 value 92.912223 iter 40 value 91.172951 iter 50 value 91.158658 iter 60 value 91.158280 iter 70 value 91.156642 iter 80 value 91.154849 iter 90 value 91.154602 iter 100 value 84.668925 final value 84.668925 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 96.696162 iter 10 value 93.732499 iter 20 value 93.731234 iter 30 value 93.162495 iter 40 value 93.152119 iter 50 value 93.150646 iter 60 value 93.119935 iter 70 value 93.118396 final value 93.118394 converged Fitting Repeat 5 # weights: 507 initial value 101.095849 iter 10 value 93.691013 iter 20 value 93.689654 iter 30 value 93.678023 iter 40 value 93.557862 iter 50 value 90.285208 iter 60 value 86.932785 iter 70 value 86.804039 iter 80 value 84.677319 iter 90 value 84.418762 iter 100 value 84.395041 final value 84.395041 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 108.516102 final value 94.052910 converged Fitting Repeat 2 # weights: 103 initial value 94.929076 final value 94.052910 converged Fitting Repeat 3 # weights: 103 initial value 113.378612 final value 94.052910 converged Fitting Repeat 4 # weights: 103 initial value 103.216320 iter 10 value 91.788183 iter 20 value 87.913614 iter 30 value 85.472639 final value 85.462600 converged Fitting Repeat 5 # weights: 103 initial value 100.321100 final value 94.052910 converged Fitting Repeat 1 # weights: 305 initial value 102.858958 final value 94.052910 converged Fitting Repeat 2 # weights: 305 initial value 97.438305 final value 94.052910 converged Fitting Repeat 3 # weights: 305 initial value 97.809719 final value 93.559524 converged Fitting Repeat 4 # weights: 305 initial value 94.505800 iter 10 value 93.900469 final value 93.900002 converged Fitting Repeat 5 # weights: 305 initial value 109.140350 iter 10 value 93.877458 final value 93.582418 converged Fitting Repeat 1 # weights: 507 initial value 96.815794 final value 94.052910 converged Fitting Repeat 2 # weights: 507 initial value 107.234847 final value 93.371808 converged Fitting Repeat 3 # weights: 507 initial value 107.752817 final value 93.582418 converged Fitting Repeat 4 # weights: 507 initial value 96.588688 iter 10 value 94.053159 final value 94.052911 converged Fitting Repeat 5 # weights: 507 initial value 105.596013 final value 94.052910 converged Fitting Repeat 1 # weights: 103 initial value 122.475765 iter 10 value 94.085458 iter 20 value 93.987571 iter 30 value 88.228834 iter 40 value 86.090297 iter 50 value 85.531335 iter 60 value 85.444121 iter 70 value 85.098579 iter 80 value 84.168978 iter 90 value 83.725138 iter 100 value 83.709055 final value 83.709055 stopped after 100 iterations Fitting Repeat 2 # weights: 103 initial value 111.989242 iter 10 value 93.936793 iter 20 value 93.704371 iter 30 value 89.161044 iter 40 value 86.129724 iter 50 value 83.654560 iter 60 value 82.870816 iter 70 value 82.291039 iter 80 value 82.199161 iter 90 value 82.185272 iter 100 value 82.175650 final value 82.175650 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 97.409195 iter 10 value 94.066230 iter 20 value 93.617122 iter 30 value 92.805193 iter 40 value 91.558215 iter 50 value 87.009808 iter 60 value 86.093057 iter 70 value 85.666208 iter 80 value 83.970348 iter 90 value 83.533448 iter 100 value 83.458387 final value 83.458387 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 102.226574 iter 10 value 94.057576 iter 20 value 90.719937 iter 30 value 87.059421 iter 40 value 86.271927 iter 50 value 85.404380 iter 60 value 83.580823 iter 70 value 83.458432 final value 83.458384 converged Fitting Repeat 5 # weights: 103 initial value 101.211348 iter 10 value 94.012897 iter 20 value 89.678985 iter 30 value 88.792065 iter 40 value 88.014314 iter 50 value 85.378558 iter 60 value 84.019953 iter 70 value 83.911352 iter 80 value 83.849873 final value 83.849755 converged Fitting Repeat 1 # weights: 305 initial value 100.476278 iter 10 value 89.925890 iter 20 value 85.187510 iter 30 value 84.590245 iter 40 value 84.392084 iter 50 value 83.782236 iter 60 value 83.192838 iter 70 value 83.165911 iter 80 value 83.149381 iter 90 value 82.930538 iter 100 value 82.198929 final value 82.198929 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 123.880417 iter 10 value 94.066616 iter 20 value 89.833194 iter 30 value 86.824998 iter 40 value 86.010715 iter 50 value 84.695482 iter 60 value 83.879966 iter 70 value 83.709049 iter 80 value 83.592083 iter 90 value 83.194188 iter 100 value 82.552812 final value 82.552812 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 101.353712 iter 10 value 93.548023 iter 20 value 88.788698 iter 30 value 83.518551 iter 40 value 82.371988 iter 50 value 81.564185 iter 60 value 81.023640 iter 70 value 80.753360 iter 80 value 80.575048 iter 90 value 80.330640 iter 100 value 80.216749 final value 80.216749 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 104.504342 iter 10 value 94.066764 iter 20 value 94.055096 iter 30 value 93.665793 iter 40 value 93.569169 iter 50 value 89.364768 iter 60 value 83.801373 iter 70 value 81.639040 iter 80 value 80.824192 iter 90 value 80.449097 iter 100 value 80.379403 final value 80.379403 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 104.606839 iter 10 value 94.029598 iter 20 value 91.418135 iter 30 value 87.971741 iter 40 value 86.082404 iter 50 value 83.562752 iter 60 value 82.288096 iter 70 value 81.393943 iter 80 value 81.017130 iter 90 value 80.743078 iter 100 value 80.646650 final value 80.646650 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 109.054291 iter 10 value 94.142812 iter 20 value 92.260909 iter 30 value 88.038779 iter 40 value 87.706775 iter 50 value 83.175542 iter 60 value 82.113011 iter 70 value 81.255297 iter 80 value 80.516290 iter 90 value 80.166130 iter 100 value 80.066863 final value 80.066863 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 103.456004 iter 10 value 94.150967 iter 20 value 93.364261 iter 30 value 90.880988 iter 40 value 87.027165 iter 50 value 85.487786 iter 60 value 82.572916 iter 70 value 82.194044 iter 80 value 81.843526 iter 90 value 81.493936 iter 100 value 81.257280 final value 81.257280 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 116.745074 iter 10 value 94.199885 iter 20 value 94.030225 iter 30 value 87.696455 iter 40 value 86.936629 iter 50 value 84.306870 iter 60 value 82.949390 iter 70 value 82.461700 iter 80 value 82.030415 iter 90 value 81.612982 iter 100 value 81.444967 final value 81.444967 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 114.607841 iter 10 value 94.017592 iter 20 value 90.676125 iter 30 value 84.740355 iter 40 value 84.289403 iter 50 value 83.875569 iter 60 value 82.634316 iter 70 value 82.191759 iter 80 value 82.142462 iter 90 value 82.006095 iter 100 value 81.959432 final value 81.959432 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 112.359918 iter 10 value 97.427405 iter 20 value 93.044972 iter 30 value 87.275315 iter 40 value 85.467974 iter 50 value 83.748193 iter 60 value 83.192672 iter 70 value 83.159401 iter 80 value 83.034644 iter 90 value 82.944710 iter 100 value 82.302186 final value 82.302186 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.828345 final value 94.054761 converged Fitting Repeat 2 # weights: 103 initial value 109.752369 final value 94.054668 converged Fitting Repeat 3 # weights: 103 initial value 102.296579 iter 10 value 94.054273 iter 20 value 94.018026 iter 30 value 85.067631 iter 40 value 85.061849 iter 50 value 85.059346 iter 60 value 85.049751 iter 70 value 85.010898 final value 85.010879 converged Fitting Repeat 4 # weights: 103 initial value 100.003836 final value 94.054611 converged Fitting Repeat 5 # weights: 103 initial value 94.662225 final value 94.054481 converged Fitting Repeat 1 # weights: 305 initial value 102.223875 iter 10 value 93.587593 iter 20 value 93.583615 iter 30 value 93.329625 iter 40 value 85.704858 final value 85.608104 converged Fitting Repeat 2 # weights: 305 initial value 104.039308 iter 10 value 94.056822 iter 20 value 93.850276 iter 30 value 86.611021 iter 40 value 84.941012 iter 50 value 84.079905 iter 50 value 84.079905 iter 50 value 84.079905 final value 84.079905 converged Fitting Repeat 3 # weights: 305 initial value 103.764353 iter 10 value 92.742079 iter 20 value 92.740516 iter 30 value 92.452304 iter 40 value 92.379184 iter 50 value 92.345201 iter 60 value 92.329481 iter 70 value 92.325272 iter 80 value 92.004415 iter 90 value 91.944782 final value 91.943601 converged Fitting Repeat 4 # weights: 305 initial value 96.325595 iter 10 value 93.587341 iter 20 value 93.582787 iter 30 value 93.503140 iter 40 value 85.734922 iter 50 value 85.733621 iter 60 value 85.732420 iter 70 value 84.536360 final value 84.493042 converged Fitting Repeat 5 # weights: 305 initial value 107.697593 iter 10 value 94.058165 iter 20 value 94.053333 iter 20 value 94.053333 iter 20 value 94.053333 final value 94.053333 converged Fitting Repeat 1 # weights: 507 initial value 104.357159 iter 10 value 94.060686 iter 20 value 93.032642 iter 30 value 85.878163 iter 40 value 85.741476 iter 50 value 85.738126 iter 60 value 85.717743 iter 70 value 83.271058 iter 80 value 81.883634 iter 90 value 81.709416 iter 100 value 81.699764 final value 81.699764 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 115.740156 iter 10 value 88.734919 iter 20 value 88.623769 iter 30 value 88.267944 iter 40 value 87.737932 iter 50 value 87.581900 iter 60 value 87.312924 iter 70 value 86.764399 iter 80 value 86.688247 iter 90 value 86.671743 iter 100 value 84.648694 final value 84.648694 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 97.716430 iter 10 value 93.590420 iter 20 value 93.520475 iter 30 value 86.019054 iter 40 value 81.873754 iter 50 value 80.839974 iter 60 value 80.155572 iter 70 value 79.886049 final value 79.885974 converged Fitting Repeat 4 # weights: 507 initial value 96.265014 iter 10 value 94.059822 iter 20 value 93.662360 iter 30 value 93.529328 final value 93.529318 converged Fitting Repeat 5 # weights: 507 initial value 104.956157 iter 10 value 93.590421 iter 20 value 93.583275 iter 30 value 91.848315 iter 40 value 87.210851 iter 50 value 83.080726 iter 60 value 82.021488 iter 70 value 81.695496 iter 80 value 81.694466 iter 90 value 81.694281 final value 81.694085 converged Fitting Repeat 1 # weights: 103 initial value 96.557145 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 96.946175 iter 10 value 91.596920 iter 20 value 90.206192 iter 30 value 90.204831 final value 90.204782 converged Fitting Repeat 3 # weights: 103 initial value 96.530975 final value 94.484211 converged Fitting Repeat 4 # weights: 103 initial value 95.205567 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 98.263288 final value 94.484211 converged Fitting Repeat 1 # weights: 305 initial value 97.343651 final value 94.484211 converged Fitting Repeat 2 # weights: 305 initial value 99.541010 final value 94.484211 converged Fitting Repeat 3 # weights: 305 initial value 95.045220 iter 10 value 90.488290 final value 90.428592 converged Fitting Repeat 4 # weights: 305 initial value 110.066609 final value 94.291892 converged Fitting Repeat 5 # weights: 305 initial value 102.664732 final value 94.484211 converged Fitting Repeat 1 # weights: 507 initial value 105.727891 final value 94.455556 converged Fitting Repeat 2 # weights: 507 initial value 105.694459 iter 10 value 92.516953 iter 20 value 89.756787 iter 30 value 89.600574 final value 89.600566 converged Fitting Repeat 3 # weights: 507 initial value 111.855260 final value 94.484211 converged Fitting Repeat 4 # weights: 507 initial value 104.710757 final value 94.484211 converged Fitting Repeat 5 # weights: 507 initial value 107.821172 iter 10 value 94.141866 iter 20 value 93.073905 iter 30 value 93.064169 final value 93.057083 converged Fitting Repeat 1 # weights: 103 initial value 97.462006 iter 10 value 89.437128 iter 20 value 87.345333 iter 30 value 86.292518 iter 40 value 85.431699 final value 85.419740 converged Fitting Repeat 2 # weights: 103 initial value 98.627257 iter 10 value 94.518903 iter 20 value 94.487473 iter 30 value 93.828473 iter 40 value 89.044050 iter 50 value 87.034775 iter 60 value 86.086292 iter 70 value 85.501916 iter 80 value 84.975806 iter 90 value 84.657542 iter 100 value 84.643666 final value 84.643666 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 98.071085 iter 10 value 94.483511 iter 20 value 93.200534 iter 30 value 90.319788 iter 40 value 89.514030 iter 50 value 89.169166 iter 60 value 85.936885 iter 70 value 84.829004 iter 80 value 84.300365 iter 90 value 84.275112 iter 100 value 84.270907 final value 84.270907 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 109.338075 iter 10 value 94.346802 iter 20 value 88.290219 iter 30 value 87.171336 iter 40 value 86.100515 iter 50 value 85.515324 iter 60 value 85.213175 iter 70 value 85.146155 final value 85.146144 converged Fitting Repeat 5 # weights: 103 initial value 96.509348 iter 10 value 94.552725 iter 20 value 94.463484 iter 30 value 93.291695 iter 40 value 91.423524 iter 50 value 87.297269 iter 60 value 86.547649 iter 70 value 85.645572 iter 80 value 85.009043 iter 90 value 84.753513 final value 84.753071 converged Fitting Repeat 1 # weights: 305 initial value 102.423015 iter 10 value 94.140039 iter 20 value 91.054454 iter 30 value 85.757543 iter 40 value 84.787273 iter 50 value 84.314804 iter 60 value 84.138963 iter 70 value 83.453179 iter 80 value 82.566567 iter 90 value 81.943457 iter 100 value 81.571806 final value 81.571806 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 105.808623 iter 10 value 92.347182 iter 20 value 92.061722 iter 30 value 91.318579 iter 40 value 90.939019 iter 50 value 90.370440 iter 60 value 90.331254 iter 70 value 90.269722 iter 80 value 89.092647 iter 90 value 83.331852 iter 100 value 81.967792 final value 81.967792 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 100.954468 iter 10 value 94.825395 iter 20 value 94.518494 iter 30 value 94.098285 iter 40 value 90.947476 iter 50 value 90.883440 iter 60 value 90.695062 iter 70 value 87.130686 iter 80 value 86.196126 iter 90 value 85.115388 iter 100 value 83.824980 final value 83.824980 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 105.846184 iter 10 value 94.513246 iter 20 value 91.782843 iter 30 value 89.391673 iter 40 value 87.548935 iter 50 value 86.474944 iter 60 value 85.810080 iter 70 value 85.529003 iter 80 value 84.944243 iter 90 value 84.717917 iter 100 value 84.380651 final value 84.380651 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 100.626462 iter 10 value 94.512191 iter 20 value 90.875881 iter 30 value 86.753812 iter 40 value 85.391677 iter 50 value 84.855912 iter 60 value 83.779325 iter 70 value 81.727559 iter 80 value 81.180694 iter 90 value 81.057056 iter 100 value 80.869226 final value 80.869226 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 107.703384 iter 10 value 94.462946 iter 20 value 92.415227 iter 30 value 89.817057 iter 40 value 85.462089 iter 50 value 84.034572 iter 60 value 82.985022 iter 70 value 81.932481 iter 80 value 81.655772 iter 90 value 81.110091 iter 100 value 81.029147 final value 81.029147 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 103.117114 iter 10 value 93.803396 iter 20 value 91.555102 iter 30 value 90.358185 iter 40 value 89.905244 iter 50 value 86.981730 iter 60 value 85.211060 iter 70 value 84.291191 iter 80 value 83.184528 iter 90 value 83.011725 iter 100 value 82.941006 final value 82.941006 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 112.039247 iter 10 value 94.551128 iter 20 value 94.273399 iter 30 value 90.880553 iter 40 value 90.686652 iter 50 value 90.573502 iter 60 value 89.470982 iter 70 value 85.844558 iter 80 value 82.617225 iter 90 value 81.620271 iter 100 value 81.096418 final value 81.096418 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 128.679930 iter 10 value 94.816953 iter 20 value 90.716391 iter 30 value 90.320766 iter 40 value 90.052689 iter 50 value 87.743700 iter 60 value 84.593946 iter 70 value 83.989605 iter 80 value 83.775707 iter 90 value 83.575261 iter 100 value 83.239954 final value 83.239954 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 111.556002 iter 10 value 94.629700 iter 20 value 89.442519 iter 30 value 86.499819 iter 40 value 82.639723 iter 50 value 81.785834 iter 60 value 81.380786 iter 70 value 81.049501 iter 80 value 80.661382 iter 90 value 80.586571 iter 100 value 80.544192 final value 80.544192 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 98.017143 final value 94.485627 converged Fitting Repeat 2 # weights: 103 initial value 96.199179 final value 94.486068 converged Fitting Repeat 3 # weights: 103 initial value 94.769613 final value 93.940791 converged Fitting Repeat 4 # weights: 103 initial value 98.555750 final value 94.485653 converged Fitting Repeat 5 # weights: 103 initial value 96.297039 final value 94.486129 converged Fitting Repeat 1 # weights: 305 initial value 116.501621 iter 10 value 94.296850 final value 94.296272 converged Fitting Repeat 2 # weights: 305 initial value 132.091741 iter 10 value 94.488988 iter 20 value 94.484193 iter 30 value 93.928552 iter 40 value 91.705420 iter 50 value 91.687967 iter 60 value 91.687196 final value 91.686915 converged Fitting Repeat 3 # weights: 305 initial value 96.004967 iter 10 value 94.486984 iter 20 value 94.464857 iter 30 value 94.294348 iter 40 value 93.941921 iter 50 value 89.156075 iter 60 value 88.180993 final value 88.124238 converged Fitting Repeat 4 # weights: 305 initial value 98.566910 iter 10 value 94.306240 iter 20 value 94.296824 iter 30 value 94.283982 iter 40 value 86.253360 iter 50 value 85.345017 iter 60 value 85.339789 iter 70 value 85.018704 iter 80 value 85.014489 final value 85.014405 converged Fitting Repeat 5 # weights: 305 initial value 99.933721 iter 10 value 94.488712 iter 20 value 93.658464 iter 30 value 90.229889 iter 40 value 85.901566 iter 50 value 85.808941 iter 60 value 83.147344 iter 70 value 82.140433 iter 80 value 82.131386 iter 90 value 82.128324 iter 100 value 82.117662 final value 82.117662 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 100.623274 iter 10 value 94.300059 iter 20 value 94.292221 final value 94.292169 converged Fitting Repeat 2 # weights: 507 initial value 104.162142 iter 10 value 94.264324 iter 20 value 94.259495 iter 30 value 94.256726 iter 30 value 94.256726 iter 30 value 94.256726 final value 94.256726 converged Fitting Repeat 3 # weights: 507 initial value 98.432907 iter 10 value 94.490971 iter 20 value 93.031543 iter 30 value 88.936918 iter 40 value 88.744427 iter 50 value 88.740305 iter 60 value 87.453404 iter 70 value 83.124156 iter 80 value 83.017909 iter 90 value 83.007808 iter 100 value 82.993687 final value 82.993687 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 113.782466 iter 10 value 90.610949 iter 20 value 84.742460 iter 30 value 84.676805 iter 40 value 84.430873 iter 50 value 84.417790 iter 60 value 84.238335 iter 70 value 83.262761 iter 80 value 82.760122 iter 90 value 82.355248 iter 100 value 81.813680 final value 81.813680 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 99.827898 iter 10 value 91.236052 iter 20 value 90.624862 iter 30 value 90.615374 final value 90.614572 converged Fitting Repeat 1 # weights: 103 initial value 109.083641 final value 94.484211 converged Fitting Repeat 2 # weights: 103 initial value 107.240936 final value 94.484211 converged Fitting Repeat 3 # weights: 103 initial value 98.412226 iter 10 value 93.283769 iter 20 value 83.962721 iter 30 value 82.218600 iter 40 value 82.218329 final value 82.218018 converged Fitting Repeat 4 # weights: 103 initial value 103.113820 final value 94.484211 converged Fitting Repeat 5 # weights: 103 initial value 96.724319 final value 93.772973 converged Fitting Repeat 1 # weights: 305 initial value 99.943855 iter 10 value 93.822256 final value 93.772973 converged Fitting Repeat 2 # weights: 305 initial value 101.786673 iter 10 value 87.579508 iter 20 value 85.426541 iter 30 value 80.976233 iter 40 value 78.937465 iter 50 value 78.486471 iter 60 value 78.133290 iter 70 value 78.123729 iter 80 value 78.105251 iter 90 value 78.071200 iter 100 value 78.030795 final value 78.030795 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 102.371913 iter 10 value 94.484313 iter 20 value 93.780319 iter 30 value 93.774833 final value 93.772973 converged Fitting Repeat 4 # weights: 305 initial value 103.547793 iter 10 value 93.766151 iter 20 value 92.124317 iter 30 value 91.967045 iter 30 value 91.967044 iter 30 value 91.967044 final value 91.967044 converged Fitting Repeat 5 # weights: 305 initial value 97.732808 final value 93.701657 converged Fitting Repeat 1 # weights: 507 initial value 100.713754 iter 10 value 91.482445 final value 91.480568 converged Fitting Repeat 2 # weights: 507 initial value 99.903740 iter 10 value 93.772975 final value 93.772973 converged Fitting Repeat 3 # weights: 507 initial value 96.352478 final value 94.448052 converged Fitting Repeat 4 # weights: 507 initial value 96.683452 iter 10 value 93.750754 iter 20 value 93.720969 final value 93.720301 converged Fitting Repeat 5 # weights: 507 initial value 115.317953 final value 94.484211 converged Fitting Repeat 1 # weights: 103 initial value 110.009961 iter 10 value 94.458646 iter 20 value 86.568603 iter 30 value 85.769847 iter 40 value 85.553825 iter 50 value 83.209407 iter 60 value 82.192176 iter 70 value 82.023624 iter 80 value 81.907910 final value 81.904632 converged Fitting Repeat 2 # weights: 103 initial value 101.548008 iter 10 value 94.488612 iter 10 value 94.488612 iter 20 value 94.289677 iter 30 value 94.108689 iter 40 value 93.938068 iter 50 value 92.747616 iter 60 value 83.935470 iter 70 value 82.856262 iter 80 value 82.389275 iter 90 value 82.344909 iter 100 value 82.208673 final value 82.208673 stopped after 100 iterations Fitting Repeat 3 # weights: 103 initial value 99.799205 iter 10 value 94.489279 iter 20 value 94.427009 iter 30 value 86.092300 iter 40 value 85.701812 iter 50 value 84.179382 iter 60 value 83.699340 iter 70 value 81.947980 iter 80 value 81.010490 iter 90 value 80.328168 iter 100 value 79.932743 final value 79.932743 stopped after 100 iterations Fitting Repeat 4 # weights: 103 initial value 97.580735 iter 10 value 94.499580 iter 20 value 87.862834 iter 30 value 83.320174 iter 40 value 82.522521 iter 50 value 81.991556 iter 60 value 81.631765 iter 70 value 81.480577 final value 81.480049 converged Fitting Repeat 5 # weights: 103 initial value 104.057938 iter 10 value 94.728999 iter 20 value 94.499508 iter 30 value 94.486311 iter 40 value 93.984598 iter 50 value 93.976186 iter 60 value 93.956037 iter 70 value 87.604454 iter 80 value 84.355755 iter 90 value 82.149257 iter 100 value 80.854472 final value 80.854472 stopped after 100 iterations Fitting Repeat 1 # weights: 305 initial value 103.639235 iter 10 value 94.453092 iter 20 value 92.891591 iter 30 value 85.827408 iter 40 value 84.073764 iter 50 value 81.486170 iter 60 value 80.247325 iter 70 value 79.628983 iter 80 value 79.533734 iter 90 value 79.445654 iter 100 value 79.373605 final value 79.373605 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 116.491370 iter 10 value 94.428453 iter 20 value 92.317643 iter 30 value 91.142698 iter 40 value 90.993002 iter 50 value 84.222750 iter 60 value 82.102574 iter 70 value 80.571043 iter 80 value 80.095055 iter 90 value 79.918043 iter 100 value 79.826718 final value 79.826718 stopped after 100 iterations Fitting Repeat 3 # weights: 305 initial value 117.439368 iter 10 value 93.965183 iter 20 value 92.944290 iter 30 value 87.650477 iter 40 value 85.679440 iter 50 value 84.175653 iter 60 value 82.589092 iter 70 value 82.034506 iter 80 value 81.861655 iter 90 value 81.713980 iter 100 value 79.771467 final value 79.771467 stopped after 100 iterations Fitting Repeat 4 # weights: 305 initial value 100.029428 iter 10 value 93.861652 iter 20 value 84.614902 iter 30 value 82.010984 iter 40 value 80.489409 iter 50 value 79.703202 iter 60 value 79.080392 iter 70 value 78.544362 iter 80 value 78.506616 iter 90 value 78.456357 iter 100 value 78.336130 final value 78.336130 stopped after 100 iterations Fitting Repeat 5 # weights: 305 initial value 111.225974 iter 10 value 94.504849 iter 20 value 94.406966 iter 30 value 94.016500 iter 40 value 85.291943 iter 50 value 83.415318 iter 60 value 83.006326 iter 70 value 81.171771 iter 80 value 80.000115 iter 90 value 79.532733 iter 100 value 79.480641 final value 79.480641 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 103.672954 iter 10 value 94.037468 iter 20 value 88.451822 iter 30 value 85.762624 iter 40 value 85.142509 iter 50 value 82.853060 iter 60 value 82.235952 iter 70 value 81.700638 iter 80 value 81.480675 iter 90 value 81.090876 iter 100 value 79.802569 final value 79.802569 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 126.943965 iter 10 value 94.487719 iter 20 value 94.118900 iter 30 value 88.190361 iter 40 value 83.240198 iter 50 value 82.772897 iter 60 value 82.381531 iter 70 value 81.914394 iter 80 value 79.542960 iter 90 value 78.740170 iter 100 value 78.503978 final value 78.503978 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 110.189140 iter 10 value 95.765125 iter 20 value 94.520350 iter 30 value 84.909618 iter 40 value 83.347066 iter 50 value 83.043925 iter 60 value 82.150393 iter 70 value 80.505635 iter 80 value 79.575748 iter 90 value 78.129635 iter 100 value 77.923344 final value 77.923344 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 104.481175 iter 10 value 94.298954 iter 20 value 94.046965 iter 30 value 93.909592 iter 40 value 93.080280 iter 50 value 88.347673 iter 60 value 84.098989 iter 70 value 81.720267 iter 80 value 80.980075 iter 90 value 80.776793 iter 100 value 79.546411 final value 79.546411 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 109.190338 iter 10 value 86.078863 iter 20 value 80.133438 iter 30 value 79.071575 iter 40 value 78.551013 iter 50 value 77.915030 iter 60 value 77.790143 iter 70 value 77.712000 iter 80 value 77.439851 iter 90 value 77.342544 iter 100 value 77.294032 final value 77.294032 stopped after 100 iterations Fitting Repeat 1 # weights: 103 initial value 95.293210 final value 94.485953 converged Fitting Repeat 2 # weights: 103 initial value 99.857852 final value 94.485953 converged Fitting Repeat 3 # weights: 103 initial value 101.037784 final value 94.486046 converged Fitting Repeat 4 # weights: 103 initial value 95.237207 final value 94.485811 converged Fitting Repeat 5 # weights: 103 initial value 99.268824 final value 94.485893 converged Fitting Repeat 1 # weights: 305 initial value 107.656159 iter 10 value 94.489486 iter 20 value 93.998899 iter 30 value 85.423916 iter 40 value 84.125294 iter 50 value 83.027562 iter 60 value 78.196709 iter 70 value 78.052511 iter 80 value 78.046773 iter 90 value 78.027533 iter 100 value 77.752638 final value 77.752638 stopped after 100 iterations Fitting Repeat 2 # weights: 305 initial value 99.129661 iter 10 value 94.218858 iter 20 value 93.795561 iter 30 value 86.171201 iter 40 value 84.542555 iter 50 value 84.509124 iter 60 value 84.434112 iter 70 value 84.398329 final value 84.398248 converged Fitting Repeat 3 # weights: 305 initial value 108.347185 iter 10 value 82.807918 iter 20 value 82.318028 iter 30 value 82.242372 iter 40 value 81.437543 iter 50 value 81.315585 final value 81.315582 converged Fitting Repeat 4 # weights: 305 initial value 102.674294 iter 10 value 89.161995 iter 20 value 86.522059 final value 86.518585 converged Fitting Repeat 5 # weights: 305 initial value 96.940447 iter 10 value 94.453029 iter 20 value 94.448217 iter 30 value 93.226189 iter 40 value 85.004067 iter 50 value 84.989796 iter 60 value 84.962551 iter 70 value 84.670325 iter 80 value 84.583619 iter 90 value 84.570656 iter 100 value 83.738606 final value 83.738606 stopped after 100 iterations Fitting Repeat 1 # weights: 507 initial value 107.960507 iter 10 value 93.784037 iter 20 value 93.782197 iter 30 value 93.020048 iter 40 value 91.528848 iter 50 value 85.310120 iter 60 value 84.056405 iter 70 value 84.055542 iter 80 value 84.054142 iter 90 value 83.732002 iter 100 value 81.759461 final value 81.759461 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 115.917045 iter 10 value 94.113984 iter 20 value 94.108259 iter 30 value 93.717650 iter 40 value 87.198342 iter 50 value 82.101652 iter 60 value 81.565837 iter 70 value 81.552186 final value 81.552036 converged Fitting Repeat 3 # weights: 507 initial value 103.232575 iter 10 value 93.291866 iter 20 value 85.371469 iter 30 value 85.256647 iter 40 value 84.139580 iter 50 value 83.696421 iter 60 value 83.613778 iter 70 value 83.612197 iter 80 value 83.609428 iter 90 value 83.481059 iter 100 value 83.456393 final value 83.456393 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 94.919477 iter 10 value 93.649189 iter 20 value 93.628325 iter 30 value 93.626645 iter 40 value 93.565680 iter 50 value 93.557954 final value 93.557899 converged Fitting Repeat 5 # weights: 507 initial value 97.872622 iter 10 value 94.487365 iter 20 value 94.484724 iter 30 value 94.484520 iter 30 value 94.484520 iter 30 value 94.484520 final value 94.484520 converged Fitting Repeat 1 # weights: 507 initial value 129.427406 iter 10 value 117.830400 iter 20 value 108.215892 iter 30 value 105.820177 iter 40 value 105.187131 iter 50 value 103.089761 iter 60 value 102.245819 iter 70 value 101.630703 iter 80 value 101.415993 iter 90 value 100.643403 iter 100 value 100.497303 final value 100.497303 stopped after 100 iterations Fitting Repeat 2 # weights: 507 initial value 130.336630 iter 10 value 114.250230 iter 20 value 109.443811 iter 30 value 108.440170 iter 40 value 106.454521 iter 50 value 105.038844 iter 60 value 102.893169 iter 70 value 102.627673 iter 80 value 102.324975 iter 90 value 101.973030 iter 100 value 101.834463 final value 101.834463 stopped after 100 iterations Fitting Repeat 3 # weights: 507 initial value 128.580138 iter 10 value 117.967453 iter 20 value 108.102289 iter 30 value 106.527972 iter 40 value 104.333989 iter 50 value 103.720528 iter 60 value 103.164592 iter 70 value 102.903146 iter 80 value 102.482591 iter 90 value 101.576098 iter 100 value 101.213338 final value 101.213338 stopped after 100 iterations Fitting Repeat 4 # weights: 507 initial value 157.125226 iter 10 value 117.249351 iter 20 value 114.533827 iter 30 value 114.052928 iter 40 value 111.561275 iter 50 value 107.082568 iter 60 value 104.817802 iter 70 value 104.383296 iter 80 value 104.050925 iter 90 value 103.702283 iter 100 value 103.138758 final value 103.138758 stopped after 100 iterations Fitting Repeat 5 # weights: 507 initial value 141.749651 iter 10 value 119.533576 iter 20 value 108.923423 iter 30 value 106.091437 iter 40 value 105.554125 iter 50 value 103.490161 iter 60 value 103.038788 iter 70 value 102.723269 iter 80 value 102.141440 iter 90 value 101.756262 iter 100 value 101.641881 final value 101.641881 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 -- Sat May 4 04:30:34 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 45.34 1.96 46.87
HPiP.Rcheck/HPiP-Ex.timings
name | user | system | elapsed | |
FSmethod | 32.00 | 2.14 | 34.22 | |
FreqInteractors | 0.25 | 0.01 | 0.28 | |
calculateAAC | 0.06 | 0.00 | 0.06 | |
calculateAutocor | 0.41 | 0.19 | 0.59 | |
calculateCTDC | 0.11 | 0.00 | 0.11 | |
calculateCTDD | 0.57 | 0.06 | 0.64 | |
calculateCTDT | 0.36 | 0.04 | 0.39 | |
calculateCTriad | 0.49 | 0.06 | 0.55 | |
calculateDC | 0.14 | 0.00 | 0.14 | |
calculateF | 0.36 | 0.01 | 0.37 | |
calculateKSAAP | 0.14 | 0.02 | 0.15 | |
calculateQD_Sm | 1.85 | 0.20 | 2.05 | |
calculateTC | 1.39 | 0.23 | 1.63 | |
calculateTC_Sm | 0.29 | 0.02 | 0.31 | |
corr_plot | 29.71 | 2.03 | 31.73 | |
enrichfindP | 0.58 | 0.22 | 17.82 | |
enrichfind_hp | 0.12 | 0.00 | 1.09 | |
enrichplot | 0.45 | 0.00 | 0.45 | |
filter_missing_values | 0 | 0 | 0 | |
getFASTA | 0.02 | 0.00 | 2.14 | |
getHPI | 0 | 0 | 0 | |
get_negativePPI | 0 | 0 | 0 | |
get_positivePPI | 0 | 0 | 0 | |
impute_missing_data | 0 | 0 | 0 | |
plotPPI | 0.06 | 0.00 | 0.09 | |
pred_ensembel | 14.25 | 0.64 | 10.69 | |
var_imp | 31.13 | 1.30 | 32.44 | |