Matineh Rahmatbakhsh
| Snapshot Date: 2025-08-14 13:40 -0400 (Thu, 14 Aug 2025) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_21 |
| git_last_commit: e2435b7 |
| git_last_commit_date: 2025-04-15 12:38:30 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-08-18 11:41 -0400 (Mon, 18 Aug 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4824 |
| palomino7 | Windows Server 2022 Datacenter | x64 | 4.5.1 (2025-06-13 ucrt) -- "Great Square Root" | 4566 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4604 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4545 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4579 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 997/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.14.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino7 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.14.0 |
| Command: E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.21-bioc\R\library --no-vignettes --timings HPiP_1.14.0.tar.gz |
| StartedAt: 2025-08-15 03:10:26 -0400 (Fri, 15 Aug 2025) |
| EndedAt: 2025-08-15 03:16:40 -0400 (Fri, 15 Aug 2025) |
| EllapsedTime: 374.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=E:\biocbuild\bbs-3.21-bioc\R\library --no-vignettes --timings HPiP_1.14.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'E:/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck'
* using R version 4.5.1 (2025-06-13 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* 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 '1.14.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
FSmethod 35.62 2.07 38.04
corr_plot 35.50 1.88 37.47
var_imp 35.25 1.31 36.58
pred_ensembel 14.57 0.26 13.78
enrichfindP 0.75 0.04 13.26
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
'E:/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### E:\biocbuild\bbs-3.21-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'E:/biocbuild/bbs-3.21-bioc/R/library' * installing *source* package 'HPiP' ... ** this is package 'HPiP' version '1.14.0' ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.5.1 (2025-06-13 ucrt) -- "Great Square Root"
Copyright (C) 2025 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 98.184556
final value 93.244970
converged
Fitting Repeat 2
# weights: 103
initial value 101.386934
final value 94.035088
converged
Fitting Repeat 3
# weights: 103
initial value 97.892896
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 94.358242
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 98.619451
iter 10 value 92.883517
iter 20 value 92.806871
iter 30 value 92.703372
iter 40 value 87.932368
iter 50 value 87.248306
iter 60 value 87.095951
final value 87.095875
converged
Fitting Repeat 1
# weights: 305
initial value 97.044390
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 95.860045
iter 10 value 92.452914
final value 92.390476
converged
Fitting Repeat 3
# weights: 305
initial value 97.753482
final value 93.582418
converged
Fitting Repeat 4
# weights: 305
initial value 102.247213
final value 93.582418
converged
Fitting Repeat 5
# weights: 305
initial value 111.138628
final value 93.582418
converged
Fitting Repeat 1
# weights: 507
initial value 96.482160
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 106.824319
final value 93.582418
converged
Fitting Repeat 3
# weights: 507
initial value 111.553023
iter 10 value 93.957526
iter 20 value 92.443906
final value 92.443869
converged
Fitting Repeat 4
# weights: 507
initial value 104.568700
final value 93.903984
converged
Fitting Repeat 5
# weights: 507
initial value 99.274454
iter 10 value 92.587835
iter 20 value 92.313909
final value 92.312931
converged
Fitting Repeat 1
# weights: 103
initial value 97.859426
iter 10 value 94.055598
iter 20 value 89.973011
iter 30 value 85.358113
iter 40 value 83.670557
iter 50 value 83.345972
iter 60 value 83.293613
final value 83.293288
converged
Fitting Repeat 2
# weights: 103
initial value 97.627665
iter 10 value 94.067451
iter 20 value 94.054846
iter 30 value 93.590316
iter 40 value 93.570779
iter 50 value 93.568908
iter 60 value 93.568795
iter 70 value 93.033059
iter 80 value 88.041108
iter 90 value 87.140064
iter 100 value 85.997589
final value 85.997589
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 100.414946
iter 10 value 94.047437
iter 20 value 92.320651
iter 30 value 85.881514
iter 40 value 85.351704
iter 50 value 85.152939
iter 60 value 83.898219
iter 70 value 83.591096
iter 80 value 83.461357
final value 83.461266
converged
Fitting Repeat 4
# weights: 103
initial value 97.399504
iter 10 value 93.582567
iter 20 value 92.541058
iter 30 value 86.425739
iter 40 value 85.215267
iter 50 value 84.287317
iter 60 value 82.727148
iter 70 value 82.629895
final value 82.629852
converged
Fitting Repeat 5
# weights: 103
initial value 102.782098
iter 10 value 94.033295
iter 20 value 85.921670
iter 30 value 85.377833
iter 40 value 84.569326
iter 50 value 83.500961
iter 60 value 83.478676
iter 70 value 83.461332
final value 83.461266
converged
Fitting Repeat 1
# weights: 305
initial value 99.886628
iter 10 value 93.752972
iter 20 value 93.682783
iter 30 value 92.947092
iter 40 value 87.699089
iter 50 value 84.260963
iter 60 value 83.224448
iter 70 value 82.745306
iter 80 value 82.318220
iter 90 value 82.085237
iter 100 value 81.841077
final value 81.841077
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.337680
iter 10 value 93.971349
iter 20 value 89.098847
iter 30 value 88.789746
iter 40 value 87.784782
iter 50 value 85.888820
iter 60 value 84.928746
iter 70 value 84.595390
iter 80 value 84.231990
iter 90 value 82.703797
iter 100 value 82.119984
final value 82.119984
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.074443
iter 10 value 94.072317
iter 20 value 93.740986
iter 30 value 87.357444
iter 40 value 85.276535
iter 50 value 83.530942
iter 60 value 83.270575
iter 70 value 82.944947
iter 80 value 82.045735
iter 90 value 81.600224
iter 100 value 81.298753
final value 81.298753
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 112.753442
iter 10 value 94.918020
iter 20 value 89.561348
iter 30 value 85.716080
iter 40 value 85.357019
iter 50 value 83.967668
iter 60 value 83.457979
iter 70 value 83.358886
iter 80 value 83.229249
iter 90 value 82.722969
iter 100 value 81.565053
final value 81.565053
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 98.460036
iter 10 value 92.362142
iter 20 value 86.659636
iter 30 value 85.065494
iter 40 value 82.264973
iter 50 value 81.922562
iter 60 value 81.712931
iter 70 value 81.630764
iter 80 value 81.572566
iter 90 value 81.526417
iter 100 value 81.522195
final value 81.522195
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 126.792808
iter 10 value 94.458451
iter 20 value 91.575047
iter 30 value 90.585962
iter 40 value 88.366125
iter 50 value 87.474075
iter 60 value 86.845553
iter 70 value 86.010408
iter 80 value 83.382815
iter 90 value 82.170323
iter 100 value 81.619533
final value 81.619533
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.080869
iter 10 value 93.952997
iter 20 value 93.103516
iter 30 value 90.052438
iter 40 value 86.438377
iter 50 value 83.975058
iter 60 value 82.683712
iter 70 value 82.389315
iter 80 value 82.295177
iter 90 value 82.239176
iter 100 value 82.133532
final value 82.133532
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.152234
iter 10 value 94.205334
iter 20 value 94.065146
iter 30 value 93.877069
iter 40 value 92.957063
iter 50 value 92.127919
iter 60 value 86.476872
iter 70 value 86.023913
iter 80 value 85.822071
iter 90 value 85.434663
iter 100 value 83.263512
final value 83.263512
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 132.801343
iter 10 value 94.525021
iter 20 value 94.034996
iter 30 value 88.989606
iter 40 value 86.328142
iter 50 value 85.157325
iter 60 value 84.605060
iter 70 value 83.950075
iter 80 value 83.742775
iter 90 value 83.345961
iter 100 value 82.608148
final value 82.608148
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.676229
iter 10 value 94.360776
iter 20 value 93.183688
iter 30 value 86.918762
iter 40 value 85.157590
iter 50 value 84.937476
iter 60 value 83.954584
iter 70 value 83.224259
iter 80 value 83.003597
iter 90 value 82.969084
iter 100 value 82.945962
final value 82.945962
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.904268
iter 10 value 93.584392
iter 20 value 93.583276
final value 93.582736
converged
Fitting Repeat 2
# weights: 103
initial value 96.964141
final value 94.054893
converged
Fitting Repeat 3
# weights: 103
initial value 96.996143
final value 94.054393
converged
Fitting Repeat 4
# weights: 103
initial value 104.288241
final value 94.054713
converged
Fitting Repeat 5
# weights: 103
initial value 107.791109
iter 10 value 94.054833
iter 20 value 94.053007
final value 94.052915
converged
Fitting Repeat 1
# weights: 305
initial value 101.892769
iter 10 value 93.908841
iter 20 value 93.479999
iter 30 value 87.038698
final value 87.024162
converged
Fitting Repeat 2
# weights: 305
initial value 110.447652
iter 10 value 93.587420
iter 20 value 93.584019
final value 93.583118
converged
Fitting Repeat 3
# weights: 305
initial value 108.670112
iter 10 value 94.057503
iter 20 value 90.452930
iter 30 value 87.513518
iter 40 value 84.540480
iter 50 value 84.100820
iter 60 value 84.099878
iter 70 value 83.046185
iter 80 value 83.013678
iter 90 value 82.991954
final value 82.991167
converged
Fitting Repeat 4
# weights: 305
initial value 99.689590
iter 10 value 92.897899
iter 20 value 92.571840
iter 30 value 91.082249
iter 40 value 90.477955
iter 50 value 90.125349
iter 60 value 90.025147
iter 70 value 90.024337
iter 80 value 90.023152
final value 90.023085
converged
Fitting Repeat 5
# weights: 305
initial value 105.808807
iter 10 value 94.024410
iter 20 value 94.011061
iter 30 value 94.006452
iter 40 value 86.039733
iter 50 value 85.037408
iter 60 value 84.804961
iter 70 value 84.804483
iter 80 value 84.804211
iter 90 value 84.803977
iter 100 value 84.536552
final value 84.536552
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 123.645638
iter 10 value 93.854310
iter 20 value 92.713203
iter 30 value 92.257161
iter 40 value 92.239598
iter 50 value 92.006104
iter 60 value 92.002664
iter 70 value 92.001396
iter 80 value 92.000659
final value 92.000562
converged
Fitting Repeat 2
# weights: 507
initial value 97.148443
iter 10 value 94.055805
iter 20 value 93.810463
iter 30 value 93.482294
iter 40 value 93.465068
iter 50 value 93.464673
iter 60 value 92.636593
iter 70 value 92.401124
iter 80 value 92.391714
iter 80 value 92.391713
iter 80 value 92.391713
final value 92.391713
converged
Fitting Repeat 3
# weights: 507
initial value 102.702226
iter 10 value 93.474685
iter 20 value 93.472114
iter 30 value 93.470598
iter 40 value 93.469868
iter 50 value 88.597288
iter 60 value 84.921854
iter 70 value 83.405234
iter 80 value 82.500126
iter 90 value 82.465996
final value 82.464671
converged
Fitting Repeat 4
# weights: 507
initial value 99.243931
iter 10 value 89.900691
iter 20 value 88.629695
iter 30 value 88.623857
iter 40 value 88.616868
iter 50 value 88.577422
iter 60 value 88.337174
final value 88.337011
converged
Fitting Repeat 5
# weights: 507
initial value 95.665300
iter 10 value 93.912011
iter 20 value 93.661020
iter 30 value 87.400141
iter 40 value 84.762108
iter 50 value 82.659377
iter 60 value 82.605441
iter 70 value 82.484305
iter 80 value 82.452405
iter 90 value 80.893766
iter 100 value 80.321595
final value 80.321595
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.057639
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 119.481438
iter 10 value 94.276547
final value 94.275362
converged
Fitting Repeat 3
# weights: 103
initial value 103.173763
final value 94.275362
converged
Fitting Repeat 4
# weights: 103
initial value 99.153980
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 105.043748
iter 10 value 94.063425
iter 20 value 94.055059
iter 30 value 94.027811
final value 94.027742
converged
Fitting Repeat 1
# weights: 305
initial value 104.709831
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 96.095234
final value 94.275362
converged
Fitting Repeat 3
# weights: 305
initial value 105.086966
final value 94.275362
converged
Fitting Repeat 4
# weights: 305
initial value 99.733894
final value 94.083671
converged
Fitting Repeat 5
# weights: 305
initial value 98.711527
iter 10 value 93.859849
iter 10 value 93.859849
iter 10 value 93.859849
final value 93.859849
converged
Fitting Repeat 1
# weights: 507
initial value 104.995915
iter 10 value 94.064727
final value 94.057225
converged
Fitting Repeat 2
# weights: 507
initial value 94.762565
final value 94.083671
converged
Fitting Repeat 3
# weights: 507
initial value 103.381388
final value 94.443243
converged
Fitting Repeat 4
# weights: 507
initial value 98.733900
iter 10 value 94.312038
iter 10 value 94.312038
iter 10 value 94.312038
final value 94.312038
converged
Fitting Repeat 5
# weights: 507
initial value 96.334669
final value 94.275370
converged
Fitting Repeat 1
# weights: 103
initial value 97.914761
iter 10 value 94.486458
iter 20 value 94.341735
iter 30 value 88.829379
iter 40 value 82.925015
iter 50 value 82.476346
iter 60 value 81.517971
iter 70 value 80.851636
iter 80 value 80.690285
iter 90 value 80.377428
final value 80.359856
converged
Fitting Repeat 2
# weights: 103
initial value 96.367429
iter 10 value 94.488731
iter 20 value 94.469051
iter 30 value 94.174162
iter 40 value 92.747107
iter 50 value 86.700081
iter 60 value 84.583364
iter 70 value 82.994969
iter 80 value 80.903737
iter 90 value 80.734888
final value 80.734441
converged
Fitting Repeat 3
# weights: 103
initial value 99.744054
iter 10 value 90.613125
iter 20 value 84.197839
iter 30 value 82.016992
iter 40 value 81.887702
iter 50 value 81.137026
iter 60 value 80.761712
iter 70 value 80.739866
iter 80 value 80.734448
final value 80.734441
converged
Fitting Repeat 4
# weights: 103
initial value 101.040668
iter 10 value 94.446506
iter 20 value 90.315207
iter 30 value 87.215015
iter 40 value 86.309962
iter 50 value 83.106928
iter 60 value 82.251340
iter 70 value 82.153786
iter 80 value 82.112740
iter 90 value 82.102795
iter 100 value 82.099390
final value 82.099390
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 97.725053
iter 10 value 94.336272
iter 20 value 94.089016
iter 30 value 86.353250
iter 40 value 84.139560
iter 50 value 82.240997
iter 60 value 81.435038
iter 70 value 80.483245
iter 80 value 80.328615
final value 80.325005
converged
Fitting Repeat 1
# weights: 305
initial value 105.758813
iter 10 value 95.080934
iter 20 value 90.212630
iter 30 value 83.054036
iter 40 value 81.713071
iter 50 value 80.862176
iter 60 value 80.011623
iter 70 value 79.893846
iter 80 value 79.852518
iter 90 value 79.663001
iter 100 value 79.165292
final value 79.165292
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 116.897322
iter 10 value 94.497228
iter 20 value 84.078765
iter 30 value 82.191718
iter 40 value 81.041061
iter 50 value 80.779977
iter 60 value 80.723922
iter 70 value 80.273637
iter 80 value 79.325876
iter 90 value 78.987888
iter 100 value 78.567327
final value 78.567327
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 133.790243
iter 10 value 94.882235
iter 20 value 86.630066
iter 30 value 82.988041
iter 40 value 81.795586
iter 50 value 81.085658
iter 60 value 81.054756
iter 70 value 81.017629
iter 80 value 80.925585
iter 90 value 79.630411
iter 100 value 78.590845
final value 78.590845
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 115.725246
iter 10 value 94.408275
iter 20 value 82.893656
iter 30 value 82.656363
iter 40 value 80.962520
iter 50 value 79.740731
iter 60 value 79.145065
iter 70 value 78.935906
iter 80 value 78.820703
iter 90 value 78.762859
iter 100 value 78.741662
final value 78.741662
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 110.642041
iter 10 value 94.442927
iter 20 value 84.999557
iter 30 value 84.091769
iter 40 value 82.102651
iter 50 value 82.018399
iter 60 value 81.911641
iter 70 value 81.844902
iter 80 value 81.825856
iter 90 value 81.705485
iter 100 value 81.263433
final value 81.263433
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.684184
iter 10 value 94.585548
iter 20 value 89.615934
iter 30 value 84.700010
iter 40 value 84.453802
iter 50 value 81.390401
iter 60 value 79.476056
iter 70 value 79.113125
iter 80 value 78.740723
iter 90 value 78.445563
iter 100 value 78.041996
final value 78.041996
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 117.774572
iter 10 value 94.471749
iter 20 value 91.795092
iter 30 value 83.538982
iter 40 value 82.885240
iter 50 value 82.634662
iter 60 value 82.058972
iter 70 value 81.882800
iter 80 value 81.592461
iter 90 value 80.416359
iter 100 value 79.826843
final value 79.826843
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.272497
iter 10 value 94.135273
iter 20 value 90.656619
iter 30 value 86.659563
iter 40 value 85.292102
iter 50 value 81.325219
iter 60 value 80.270814
iter 70 value 79.961609
iter 80 value 79.678184
iter 90 value 79.104964
iter 100 value 78.767857
final value 78.767857
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 114.440746
iter 10 value 95.012395
iter 20 value 88.026278
iter 30 value 82.820697
iter 40 value 82.427275
iter 50 value 81.427557
iter 60 value 80.644786
iter 70 value 79.799995
iter 80 value 79.272053
iter 90 value 78.566335
iter 100 value 78.323553
final value 78.323553
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.681383
iter 10 value 94.677414
iter 20 value 94.154578
iter 30 value 84.099506
iter 40 value 83.878464
iter 50 value 83.457171
iter 60 value 80.602655
iter 70 value 79.369680
iter 80 value 79.060507
iter 90 value 78.744033
iter 100 value 78.522288
final value 78.522288
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.864621
iter 10 value 94.277394
iter 20 value 94.276098
iter 30 value 88.240384
iter 40 value 86.015016
iter 50 value 85.928512
iter 60 value 85.348137
iter 70 value 85.319487
final value 85.319166
converged
Fitting Repeat 2
# weights: 103
initial value 102.746137
final value 94.485800
converged
Fitting Repeat 3
# weights: 103
initial value 103.039457
iter 10 value 94.486014
iter 20 value 94.482225
iter 30 value 94.176788
iter 40 value 94.090315
final value 94.083828
converged
Fitting Repeat 4
# weights: 103
initial value 107.471043
final value 94.485701
converged
Fitting Repeat 5
# weights: 103
initial value 111.599099
iter 10 value 94.235907
final value 94.230550
converged
Fitting Repeat 1
# weights: 305
initial value 96.185361
iter 10 value 94.455681
iter 20 value 85.235280
iter 30 value 85.172329
iter 40 value 83.808934
iter 50 value 81.541424
iter 60 value 80.483962
iter 70 value 80.401634
iter 80 value 80.399805
iter 90 value 80.398659
iter 100 value 80.305634
final value 80.305634
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 111.163264
iter 10 value 94.489024
iter 20 value 94.177017
final value 93.720498
converged
Fitting Repeat 3
# weights: 305
initial value 106.402528
iter 10 value 94.489265
iter 20 value 94.394073
iter 30 value 88.332382
iter 40 value 87.751951
iter 50 value 87.733625
iter 60 value 86.777020
iter 70 value 86.684615
iter 80 value 86.662395
iter 90 value 86.618506
iter 100 value 85.944665
final value 85.944665
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 96.022960
iter 10 value 94.037107
iter 20 value 93.382079
iter 30 value 92.211576
iter 40 value 90.875710
iter 50 value 90.387423
iter 60 value 90.386726
iter 70 value 90.385311
iter 80 value 90.300804
iter 90 value 90.106171
iter 100 value 86.804633
final value 86.804633
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.835362
iter 10 value 94.062438
iter 20 value 94.058105
iter 30 value 87.556746
iter 40 value 81.628014
iter 50 value 80.259620
iter 60 value 80.234900
iter 70 value 80.233347
iter 80 value 80.231558
iter 90 value 80.228508
iter 100 value 80.203097
final value 80.203097
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 94.818780
iter 10 value 91.727877
iter 20 value 91.347681
iter 30 value 90.935590
iter 40 value 90.385811
iter 50 value 90.384055
final value 90.383890
converged
Fitting Repeat 2
# weights: 507
initial value 107.397873
iter 10 value 93.950616
iter 20 value 92.953537
iter 30 value 85.217193
iter 40 value 85.108248
iter 50 value 80.933374
iter 60 value 80.870656
iter 70 value 80.865931
iter 80 value 80.571190
iter 90 value 80.570428
final value 80.568574
converged
Fitting Repeat 3
# weights: 507
initial value 103.862690
iter 10 value 93.868815
iter 20 value 93.866397
iter 30 value 86.642794
iter 40 value 83.681806
iter 50 value 83.675694
iter 60 value 83.675628
iter 70 value 83.477626
iter 80 value 80.007822
iter 90 value 78.077264
iter 100 value 77.695033
final value 77.695033
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 92.077059
iter 10 value 88.352324
iter 20 value 84.184477
iter 30 value 83.230363
iter 40 value 83.125306
iter 50 value 83.044943
iter 60 value 83.038736
iter 70 value 83.033627
iter 80 value 82.956315
iter 90 value 82.797935
iter 100 value 82.796263
final value 82.796263
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.744162
iter 10 value 86.485832
iter 20 value 85.425086
iter 30 value 84.941174
iter 40 value 84.911628
iter 50 value 84.909933
iter 60 value 81.374063
iter 70 value 80.740355
iter 80 value 80.736704
iter 90 value 80.620457
iter 100 value 80.397265
final value 80.397265
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.929414
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 99.494891
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.315944
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 99.919005
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.102631
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 108.198567
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 102.980386
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 109.559257
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 127.703462
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 97.019672
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 111.278138
iter 10 value 94.443453
iter 20 value 92.417371
iter 30 value 87.204856
iter 40 value 86.927352
iter 50 value 86.923188
final value 86.923168
converged
Fitting Repeat 2
# weights: 507
initial value 110.435088
iter 10 value 94.237807
iter 20 value 94.092976
final value 94.091730
converged
Fitting Repeat 3
# weights: 507
initial value 95.873266
final value 94.461538
converged
Fitting Repeat 4
# weights: 507
initial value 106.032741
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 98.022544
iter 10 value 94.144470
iter 20 value 94.091733
final value 94.091729
converged
Fitting Repeat 1
# weights: 103
initial value 97.775556
iter 10 value 93.760795
iter 20 value 90.838951
iter 30 value 89.714828
iter 40 value 86.698001
iter 50 value 84.419042
iter 60 value 84.258567
iter 70 value 84.072255
iter 80 value 83.843745
iter 90 value 83.810189
iter 100 value 83.806826
final value 83.806826
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.992125
iter 10 value 94.541077
iter 20 value 94.471038
iter 30 value 94.192426
iter 40 value 94.185360
iter 50 value 93.747222
iter 60 value 91.032871
iter 70 value 85.980092
iter 80 value 85.004885
iter 90 value 84.605945
iter 100 value 83.875038
final value 83.875038
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 101.624708
iter 10 value 94.488735
iter 20 value 94.423931
iter 30 value 91.418604
iter 40 value 87.151540
iter 50 value 84.991542
iter 60 value 83.166349
iter 70 value 82.743911
iter 80 value 82.718463
iter 90 value 82.707410
iter 100 value 82.679811
final value 82.679811
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.447659
iter 10 value 94.488870
iter 20 value 94.210921
iter 30 value 85.260114
iter 40 value 83.996211
iter 50 value 83.886688
iter 60 value 83.808280
iter 70 value 83.803047
final value 83.801955
converged
Fitting Repeat 5
# weights: 103
initial value 98.067713
iter 10 value 94.224403
iter 20 value 88.928378
iter 30 value 86.695999
iter 40 value 85.803213
iter 50 value 84.366780
iter 60 value 83.120769
iter 70 value 82.706665
iter 80 value 82.678532
final value 82.675999
converged
Fitting Repeat 1
# weights: 305
initial value 111.344745
iter 10 value 93.929742
iter 20 value 84.680596
iter 30 value 83.526013
iter 40 value 83.127822
iter 50 value 83.037075
iter 60 value 82.829010
iter 70 value 82.645193
iter 80 value 82.498216
iter 90 value 82.256160
iter 100 value 82.188032
final value 82.188032
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.037548
iter 10 value 89.619651
iter 20 value 86.221969
iter 30 value 84.238242
iter 40 value 83.931199
iter 50 value 83.776195
iter 60 value 83.767369
iter 70 value 83.615392
iter 80 value 83.048135
iter 90 value 82.554891
iter 100 value 82.189384
final value 82.189384
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.797766
iter 10 value 94.266420
iter 20 value 89.913912
iter 30 value 88.366313
iter 40 value 87.486893
iter 50 value 87.281622
iter 60 value 85.770651
iter 70 value 83.300975
iter 80 value 83.087866
iter 90 value 83.032525
iter 100 value 82.912378
final value 82.912378
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.140347
iter 10 value 94.287537
iter 20 value 88.001476
iter 30 value 85.871526
iter 40 value 84.396248
iter 50 value 83.812054
iter 60 value 83.044189
iter 70 value 82.597839
iter 80 value 81.996373
iter 90 value 81.894040
iter 100 value 81.883701
final value 81.883701
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.545365
iter 10 value 94.607215
iter 20 value 92.070771
iter 30 value 90.370990
iter 40 value 88.230826
iter 50 value 87.659153
iter 60 value 84.682593
iter 70 value 82.618385
iter 80 value 81.706814
iter 90 value 81.589198
iter 100 value 81.509759
final value 81.509759
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.871619
iter 10 value 95.186157
iter 20 value 87.642927
iter 30 value 84.452572
iter 40 value 82.375157
iter 50 value 81.895787
iter 60 value 81.693633
iter 70 value 81.629238
iter 80 value 81.570964
iter 90 value 81.541890
iter 100 value 81.510498
final value 81.510498
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.120625
iter 10 value 94.490256
iter 20 value 94.060079
iter 30 value 93.546273
iter 40 value 88.491934
iter 50 value 85.113941
iter 60 value 84.394145
iter 70 value 83.477975
iter 80 value 82.534218
iter 90 value 82.282479
iter 100 value 82.217863
final value 82.217863
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.302768
iter 10 value 92.131031
iter 20 value 87.395215
iter 30 value 86.811243
iter 40 value 86.737470
iter 50 value 86.493165
iter 60 value 83.703376
iter 70 value 82.866162
iter 80 value 82.826611
iter 90 value 82.786760
iter 100 value 82.597817
final value 82.597817
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.429008
iter 10 value 96.033572
iter 20 value 88.065240
iter 30 value 87.160000
iter 40 value 84.304006
iter 50 value 83.486562
iter 60 value 82.318969
iter 70 value 82.037476
iter 80 value 81.971346
iter 90 value 81.857808
iter 100 value 81.736231
final value 81.736231
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 111.006280
iter 10 value 94.442410
iter 20 value 94.173421
iter 30 value 93.608462
iter 40 value 89.795448
iter 50 value 87.584051
iter 60 value 86.028449
iter 70 value 82.211961
iter 80 value 82.054048
iter 90 value 81.846690
iter 100 value 81.752994
final value 81.752994
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 107.133569
iter 10 value 94.486064
iter 20 value 94.482742
iter 30 value 94.284775
iter 40 value 86.178339
iter 50 value 85.281888
iter 60 value 84.949855
iter 70 value 84.937368
final value 84.937297
converged
Fitting Repeat 2
# weights: 103
initial value 95.404575
final value 94.486015
converged
Fitting Repeat 3
# weights: 103
initial value 96.911753
final value 94.485735
converged
Fitting Repeat 4
# weights: 103
initial value 120.045505
final value 94.485815
converged
Fitting Repeat 5
# weights: 103
initial value 102.733732
final value 94.485862
converged
Fitting Repeat 1
# weights: 305
initial value 101.067185
iter 10 value 94.448297
iter 20 value 94.408275
final value 94.400677
converged
Fitting Repeat 2
# weights: 305
initial value 100.226397
iter 10 value 94.448179
iter 20 value 94.445496
iter 30 value 91.846958
iter 40 value 85.705813
iter 50 value 85.344669
iter 60 value 85.343663
final value 85.343653
converged
Fitting Repeat 3
# weights: 305
initial value 104.483725
iter 10 value 94.488246
iter 20 value 94.277835
iter 30 value 85.794643
iter 40 value 85.357224
iter 50 value 85.073305
iter 60 value 84.705760
final value 84.694933
converged
Fitting Repeat 4
# weights: 305
initial value 115.699290
iter 10 value 94.489361
iter 20 value 94.465689
iter 30 value 94.109030
iter 40 value 94.092997
iter 50 value 94.091848
iter 50 value 94.091847
iter 50 value 94.091847
final value 94.091847
converged
Fitting Repeat 5
# weights: 305
initial value 96.571774
iter 10 value 94.488554
iter 20 value 94.484227
final value 94.484213
converged
Fitting Repeat 1
# weights: 507
initial value 98.780098
iter 10 value 93.508169
iter 20 value 87.088572
iter 30 value 86.523406
iter 40 value 86.337384
iter 50 value 86.184022
iter 60 value 86.177932
iter 70 value 85.676961
iter 80 value 85.228207
iter 90 value 85.202480
final value 85.202181
converged
Fitting Repeat 2
# weights: 507
initial value 97.171908
iter 10 value 94.451251
iter 20 value 94.404562
final value 94.400510
converged
Fitting Repeat 3
# weights: 507
initial value 99.272633
iter 10 value 94.487660
final value 94.484224
converged
Fitting Repeat 4
# weights: 507
initial value 107.461343
iter 10 value 94.493114
iter 20 value 94.485666
iter 30 value 94.158105
final value 94.106498
converged
Fitting Repeat 5
# weights: 507
initial value 126.610913
iter 10 value 94.492630
iter 20 value 94.433435
iter 30 value 90.789299
iter 40 value 88.912259
iter 50 value 88.885233
iter 60 value 88.884991
iter 70 value 88.869530
iter 80 value 88.762728
final value 88.759685
converged
Fitting Repeat 1
# weights: 103
initial value 100.901005
final value 94.038251
converged
Fitting Repeat 2
# weights: 103
initial value 98.481002
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 106.068022
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 95.561902
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 100.172163
iter 10 value 94.038633
final value 94.038251
converged
Fitting Repeat 1
# weights: 305
initial value 103.363652
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 96.499967
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 104.055938
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 104.674771
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 109.940159
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 94.123625
final value 94.052913
converged
Fitting Repeat 2
# weights: 507
initial value 111.353202
final value 94.038251
converged
Fitting Repeat 3
# weights: 507
initial value 101.431054
final value 94.047624
converged
Fitting Repeat 4
# weights: 507
initial value 95.718742
iter 10 value 94.049007
final value 94.038251
converged
Fitting Repeat 5
# weights: 507
initial value 96.183511
final value 94.038095
converged
Fitting Repeat 1
# weights: 103
initial value 95.827393
iter 10 value 94.047352
iter 20 value 92.839872
iter 30 value 86.138116
iter 40 value 83.365612
iter 50 value 82.704042
iter 60 value 82.068952
iter 70 value 81.794761
iter 80 value 81.783885
final value 81.783801
converged
Fitting Repeat 2
# weights: 103
initial value 98.649248
iter 10 value 94.054022
iter 20 value 88.758006
iter 30 value 83.042829
iter 40 value 81.730102
iter 50 value 80.547722
iter 60 value 79.002350
iter 70 value 78.908984
iter 80 value 78.877574
final value 78.876643
converged
Fitting Repeat 3
# weights: 103
initial value 96.470958
iter 10 value 93.787477
iter 20 value 88.633687
iter 30 value 85.239310
iter 40 value 85.056521
iter 50 value 84.159712
iter 60 value 84.123378
iter 70 value 84.094433
iter 80 value 84.070986
iter 90 value 83.909735
iter 100 value 83.616634
final value 83.616634
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.303899
iter 10 value 94.019192
iter 20 value 92.742416
iter 30 value 88.839791
iter 40 value 87.998319
iter 50 value 87.475917
iter 60 value 87.474073
iter 60 value 87.474072
iter 60 value 87.474072
final value 87.474072
converged
Fitting Repeat 5
# weights: 103
initial value 95.930834
iter 10 value 94.044250
iter 20 value 88.445609
iter 30 value 84.362255
iter 40 value 83.981578
iter 50 value 83.892347
iter 60 value 83.615809
iter 70 value 83.564961
iter 80 value 83.450866
iter 90 value 83.362054
final value 83.362015
converged
Fitting Repeat 1
# weights: 305
initial value 103.152934
iter 10 value 94.628228
iter 20 value 94.399436
iter 30 value 85.463622
iter 40 value 84.011585
iter 50 value 83.799009
iter 60 value 83.009384
iter 70 value 82.353440
iter 80 value 79.983126
iter 90 value 79.607099
iter 100 value 79.248485
final value 79.248485
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 111.548297
iter 10 value 93.625273
iter 20 value 84.118604
iter 30 value 82.442101
iter 40 value 82.261706
iter 50 value 81.395041
iter 60 value 80.973941
iter 70 value 80.734085
iter 80 value 79.672136
iter 90 value 79.316460
iter 100 value 79.131237
final value 79.131237
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 137.484089
iter 10 value 93.994756
iter 20 value 88.717168
iter 30 value 87.981971
iter 40 value 86.504845
iter 50 value 86.245791
iter 60 value 86.111529
iter 70 value 84.861798
iter 80 value 82.145306
iter 90 value 80.245409
iter 100 value 79.816868
final value 79.816868
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 117.185363
iter 10 value 94.022574
iter 20 value 91.669469
iter 30 value 89.467463
iter 40 value 83.920593
iter 50 value 80.948577
iter 60 value 79.604998
iter 70 value 79.075224
iter 80 value 78.759516
iter 90 value 78.638533
iter 100 value 78.438167
final value 78.438167
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.591819
iter 10 value 94.028336
iter 20 value 91.609327
iter 30 value 82.661604
iter 40 value 80.467595
iter 50 value 79.587475
iter 60 value 79.283486
iter 70 value 78.932053
iter 80 value 78.548669
iter 90 value 78.058414
iter 100 value 77.555288
final value 77.555288
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.330055
iter 10 value 94.054755
iter 20 value 83.500825
iter 30 value 81.406595
iter 40 value 81.107015
iter 50 value 80.807004
iter 60 value 79.506500
iter 70 value 78.910559
iter 80 value 78.580889
iter 90 value 78.321066
iter 100 value 77.997450
final value 77.997450
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 112.678030
iter 10 value 94.024227
iter 20 value 89.910843
iter 30 value 86.359929
iter 40 value 85.983374
iter 50 value 81.391061
iter 60 value 80.880962
iter 70 value 80.021402
iter 80 value 79.551451
iter 90 value 78.336048
iter 100 value 78.129884
final value 78.129884
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 145.170243
iter 10 value 100.566403
iter 20 value 94.056502
iter 30 value 94.014212
iter 40 value 93.183468
iter 50 value 89.185045
iter 60 value 81.952139
iter 70 value 80.437472
iter 80 value 79.828613
iter 90 value 79.529432
iter 100 value 79.362588
final value 79.362588
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.409623
iter 10 value 95.992972
iter 20 value 88.338167
iter 30 value 87.507603
iter 40 value 86.577575
iter 50 value 84.814342
iter 60 value 82.224464
iter 70 value 82.145705
iter 80 value 79.723258
iter 90 value 78.144321
iter 100 value 77.965729
final value 77.965729
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 149.276884
iter 10 value 92.275979
iter 20 value 87.702744
iter 30 value 81.759668
iter 40 value 80.071444
iter 50 value 78.747203
iter 60 value 78.444288
iter 70 value 77.914875
iter 80 value 77.626789
iter 90 value 77.520575
iter 100 value 77.479074
final value 77.479074
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.074454
final value 94.054510
converged
Fitting Repeat 2
# weights: 103
initial value 97.313018
final value 94.054555
converged
Fitting Repeat 3
# weights: 103
initial value 106.313154
final value 94.054633
converged
Fitting Repeat 4
# weights: 103
initial value 100.980837
final value 94.054839
converged
Fitting Repeat 5
# weights: 103
initial value 104.251059
final value 94.054513
converged
Fitting Repeat 1
# weights: 305
initial value 100.325301
iter 10 value 93.841306
iter 20 value 93.838450
iter 30 value 93.838174
iter 40 value 93.837385
iter 50 value 93.837129
final value 93.837028
converged
Fitting Repeat 2
# weights: 305
initial value 100.269225
iter 10 value 93.831402
iter 20 value 93.829974
iter 30 value 93.826564
iter 40 value 93.826434
iter 50 value 93.825416
iter 60 value 88.069628
iter 70 value 85.870426
iter 80 value 85.507841
iter 90 value 85.413828
final value 85.407132
converged
Fitting Repeat 3
# weights: 305
initial value 104.258392
iter 10 value 94.057255
iter 20 value 93.978189
iter 30 value 85.121605
iter 40 value 85.118979
iter 50 value 84.943164
iter 60 value 84.841100
iter 70 value 84.839019
iter 80 value 84.148699
final value 84.118701
converged
Fitting Repeat 4
# weights: 305
initial value 100.894768
iter 10 value 94.057811
iter 20 value 94.052281
iter 30 value 94.038304
final value 94.038284
converged
Fitting Repeat 5
# weights: 305
initial value 115.244852
iter 10 value 94.057867
iter 20 value 93.944134
iter 30 value 86.711568
iter 40 value 86.709389
iter 50 value 85.409865
iter 60 value 85.409416
iter 70 value 85.406910
iter 80 value 85.406877
iter 90 value 85.406747
iter 100 value 85.378531
final value 85.378531
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 123.697973
iter 10 value 94.046268
iter 20 value 94.039260
iter 30 value 90.013711
iter 40 value 82.138499
iter 50 value 77.519238
iter 60 value 76.404704
iter 70 value 76.098867
iter 80 value 76.005052
iter 90 value 76.002175
iter 90 value 76.002174
iter 90 value 76.002174
final value 76.002174
converged
Fitting Repeat 2
# weights: 507
initial value 108.964054
iter 10 value 94.061205
iter 20 value 93.941409
iter 30 value 89.988912
iter 40 value 85.874106
iter 50 value 80.556936
iter 60 value 80.534127
iter 70 value 80.242985
iter 80 value 80.235997
iter 90 value 80.231802
iter 100 value 80.230953
final value 80.230953
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 99.796894
iter 10 value 94.060287
iter 20 value 94.052494
iter 30 value 92.905258
iter 40 value 86.488755
iter 50 value 86.366989
iter 60 value 84.691472
iter 70 value 84.069356
iter 80 value 83.931188
iter 90 value 79.934784
iter 100 value 79.927040
final value 79.927040
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 101.012890
iter 10 value 94.045119
iter 20 value 92.288659
iter 30 value 92.222213
iter 40 value 87.657121
iter 50 value 82.952909
iter 60 value 82.929671
final value 82.928930
converged
Fitting Repeat 5
# weights: 507
initial value 101.629960
iter 10 value 89.021057
iter 20 value 86.910507
iter 30 value 86.904157
iter 40 value 86.804703
iter 50 value 86.796625
iter 60 value 86.681785
iter 70 value 86.615776
iter 80 value 86.615080
iter 90 value 86.614769
iter 100 value 86.609287
final value 86.609287
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.632629
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.872375
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.994083
final value 94.354396
converged
Fitting Repeat 4
# weights: 103
initial value 103.679719
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 107.332521
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 102.041334
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 103.144455
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 103.262929
iter 10 value 92.968205
iter 20 value 92.837549
final value 92.837207
converged
Fitting Repeat 4
# weights: 305
initial value 115.276005
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 101.320085
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 107.902186
final value 94.354396
converged
Fitting Repeat 2
# weights: 507
initial value 97.751925
final value 94.354396
converged
Fitting Repeat 3
# weights: 507
initial value 94.695792
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 102.989376
final value 93.772973
converged
Fitting Repeat 5
# weights: 507
initial value 96.983186
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 100.707901
iter 10 value 94.488705
iter 20 value 94.408152
iter 30 value 94.381817
iter 40 value 90.037551
iter 50 value 89.190835
iter 60 value 85.651378
iter 70 value 84.557956
iter 80 value 84.542940
iter 90 value 84.542842
iter 90 value 84.542842
iter 90 value 84.542842
final value 84.542842
converged
Fitting Repeat 2
# weights: 103
initial value 106.795104
iter 10 value 95.043157
iter 20 value 94.487306
iter 30 value 93.758569
iter 40 value 87.653437
iter 50 value 87.190008
iter 60 value 85.771382
iter 70 value 85.201791
iter 80 value 84.775565
iter 90 value 84.665721
final value 84.665646
converged
Fitting Repeat 3
# weights: 103
initial value 98.254654
iter 10 value 93.099850
iter 20 value 87.179185
iter 30 value 86.049156
iter 40 value 85.413457
iter 50 value 84.705592
iter 60 value 84.542859
final value 84.542842
converged
Fitting Repeat 4
# weights: 103
initial value 109.230232
iter 10 value 94.463438
iter 20 value 94.058655
iter 30 value 93.974511
iter 40 value 93.734651
iter 50 value 87.479106
iter 60 value 85.527294
iter 70 value 85.286583
iter 80 value 85.051670
iter 90 value 84.945603
iter 100 value 84.818214
final value 84.818214
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 119.056106
iter 10 value 94.068101
iter 20 value 93.658587
iter 30 value 92.116339
iter 40 value 88.814153
iter 50 value 88.429294
iter 60 value 87.401242
iter 70 value 87.353480
iter 80 value 84.933316
iter 90 value 84.647571
iter 100 value 84.510740
final value 84.510740
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.417111
iter 10 value 90.468170
iter 20 value 87.854715
iter 30 value 87.426287
iter 40 value 86.741207
iter 50 value 86.421290
iter 60 value 85.226973
iter 70 value 83.548429
iter 80 value 83.099049
iter 90 value 82.706630
iter 100 value 81.984588
final value 81.984588
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.246813
iter 10 value 94.490889
iter 20 value 93.952417
iter 30 value 93.717425
iter 40 value 89.395273
iter 50 value 85.299311
iter 60 value 81.291173
iter 70 value 81.029267
iter 80 value 80.718810
iter 90 value 80.429967
iter 100 value 80.407179
final value 80.407179
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.189255
iter 10 value 94.914950
iter 20 value 94.441063
iter 30 value 89.573822
iter 40 value 87.625095
iter 50 value 82.948475
iter 60 value 81.282700
iter 70 value 81.029705
iter 80 value 80.734997
iter 90 value 80.560655
iter 100 value 80.531447
final value 80.531447
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.164573
iter 10 value 94.475224
iter 20 value 91.374589
iter 30 value 85.859154
iter 40 value 85.574417
iter 50 value 85.366556
iter 60 value 84.631663
iter 70 value 84.171317
iter 80 value 82.652168
iter 90 value 81.887280
iter 100 value 81.615184
final value 81.615184
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 119.904476
iter 10 value 94.334381
iter 20 value 88.461131
iter 30 value 87.249552
iter 40 value 84.693739
iter 50 value 82.061671
iter 60 value 81.495489
iter 70 value 81.396647
iter 80 value 81.109900
iter 90 value 81.078688
iter 100 value 81.072231
final value 81.072231
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.329544
iter 10 value 94.817705
iter 20 value 94.431421
iter 30 value 94.010228
iter 40 value 92.163507
iter 50 value 91.672963
iter 60 value 91.429701
iter 70 value 85.557098
iter 80 value 84.176553
iter 90 value 82.894207
iter 100 value 81.484195
final value 81.484195
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.270017
iter 10 value 96.156744
iter 20 value 94.645960
iter 30 value 91.165334
iter 40 value 86.461063
iter 50 value 85.921043
iter 60 value 85.473783
iter 70 value 85.098769
iter 80 value 82.562288
iter 90 value 81.216768
iter 100 value 81.015378
final value 81.015378
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.743889
iter 10 value 94.465685
iter 20 value 88.887945
iter 30 value 82.159641
iter 40 value 80.286227
iter 50 value 80.094854
iter 60 value 79.914843
iter 70 value 79.645517
iter 80 value 79.596718
iter 90 value 79.524277
iter 100 value 79.467197
final value 79.467197
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.884558
iter 10 value 94.494520
iter 20 value 93.377703
iter 30 value 88.365188
iter 40 value 86.116006
iter 50 value 85.016774
iter 60 value 84.371766
iter 70 value 83.962135
iter 80 value 83.544371
iter 90 value 82.356842
iter 100 value 81.462481
final value 81.462481
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 138.514733
iter 10 value 94.619790
iter 20 value 94.366446
iter 30 value 92.515374
iter 40 value 91.207323
iter 50 value 86.363665
iter 60 value 85.637038
iter 70 value 84.152797
iter 80 value 82.693332
iter 90 value 82.206155
iter 100 value 81.314117
final value 81.314117
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.715071
iter 10 value 94.356329
iter 20 value 94.354709
iter 30 value 94.008357
iter 40 value 94.003139
final value 94.003135
converged
Fitting Repeat 2
# weights: 103
initial value 100.529512
iter 10 value 94.485872
final value 94.484218
converged
Fitting Repeat 3
# weights: 103
initial value 98.569813
iter 10 value 94.356187
iter 20 value 94.354506
iter 30 value 91.854849
iter 40 value 89.133252
iter 50 value 89.075105
iter 60 value 88.396059
iter 70 value 86.738445
iter 80 value 86.737019
iter 90 value 86.736262
iter 100 value 86.734199
final value 86.734199
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.957750
final value 94.356021
converged
Fitting Repeat 5
# weights: 103
initial value 97.351967
final value 94.485971
converged
Fitting Repeat 1
# weights: 305
initial value 106.349184
iter 10 value 94.488965
iter 20 value 94.484258
final value 94.484219
converged
Fitting Repeat 2
# weights: 305
initial value 104.717968
iter 10 value 94.488956
iter 20 value 94.484411
iter 30 value 94.354649
final value 94.354579
converged
Fitting Repeat 3
# weights: 305
initial value 116.043532
iter 10 value 94.489323
iter 20 value 94.478605
iter 30 value 88.723200
iter 40 value 84.997788
iter 50 value 83.558438
iter 60 value 83.557296
final value 83.557229
converged
Fitting Repeat 4
# weights: 305
initial value 96.640701
iter 10 value 93.560457
iter 20 value 85.418445
iter 30 value 85.147882
iter 40 value 85.053152
iter 40 value 85.053152
final value 85.053152
converged
Fitting Repeat 5
# weights: 305
initial value 104.082972
iter 10 value 94.359540
iter 20 value 94.354758
final value 94.354493
converged
Fitting Repeat 1
# weights: 507
initial value 115.306638
iter 10 value 94.364015
iter 20 value 94.356496
iter 30 value 90.515574
iter 40 value 85.485390
iter 50 value 85.448632
iter 60 value 85.434592
iter 70 value 85.420566
iter 70 value 85.420566
final value 85.420566
converged
Fitting Repeat 2
# weights: 507
initial value 101.931072
iter 10 value 93.220131
iter 20 value 93.213111
iter 30 value 92.015591
iter 40 value 85.483454
iter 50 value 80.348078
iter 60 value 79.468629
iter 70 value 79.401204
iter 80 value 79.400798
iter 90 value 79.158076
iter 100 value 79.077087
final value 79.077087
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.970869
iter 10 value 94.434331
iter 20 value 94.425372
iter 30 value 94.354408
iter 40 value 93.685018
iter 50 value 93.654815
iter 60 value 92.040483
iter 70 value 84.204748
iter 80 value 84.192659
iter 90 value 82.784546
iter 100 value 82.135502
final value 82.135502
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.409203
iter 10 value 94.491984
iter 20 value 93.880315
iter 30 value 93.642980
iter 40 value 93.629851
iter 50 value 93.594910
iter 60 value 86.768785
iter 70 value 85.340028
iter 80 value 84.797091
final value 84.797059
converged
Fitting Repeat 5
# weights: 507
initial value 104.195027
iter 10 value 94.475192
iter 20 value 94.208475
iter 30 value 93.948709
iter 40 value 89.772380
iter 50 value 82.699869
iter 60 value 82.320424
iter 70 value 81.139600
iter 80 value 80.721613
iter 90 value 80.720973
iter 100 value 80.710855
final value 80.710855
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 118.272040
iter 10 value 117.890929
iter 20 value 117.862924
iter 30 value 116.925717
final value 116.904271
converged
Fitting Repeat 2
# weights: 305
initial value 129.480059
iter 10 value 117.895383
iter 20 value 117.873211
iter 30 value 107.025021
final value 107.007434
converged
Fitting Repeat 3
# weights: 305
initial value 121.287971
iter 10 value 117.898241
iter 20 value 117.893213
final value 117.893207
converged
Fitting Repeat 4
# weights: 305
initial value 120.023649
iter 10 value 117.894993
iter 20 value 115.326718
iter 30 value 108.426795
iter 40 value 108.401395
iter 50 value 108.147409
iter 60 value 108.094972
final value 108.094764
converged
Fitting Repeat 5
# weights: 305
initial value 124.761482
iter 10 value 117.894995
iter 20 value 117.697409
iter 30 value 117.607563
iter 40 value 115.216350
iter 50 value 113.584454
final value 113.452248
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Fri Aug 15 03:16:30 2025
***********************************************
Number of test functions: 7
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7
Number of errors: 0
Number of failures: 0
Warning messages:
1: `repeats` has no meaning for this resampling method.
2: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
44.76 1.40 102.84
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 35.62 | 2.07 | 38.04 | |
| FreqInteractors | 0.33 | 0.02 | 0.36 | |
| calculateAAC | 0.04 | 0.01 | 0.06 | |
| calculateAutocor | 0.50 | 0.08 | 0.58 | |
| calculateCTDC | 0.11 | 0.00 | 0.11 | |
| calculateCTDD | 0.92 | 0.09 | 1.02 | |
| calculateCTDT | 0.41 | 0.00 | 0.41 | |
| calculateCTriad | 0.47 | 0.05 | 0.51 | |
| calculateDC | 0.12 | 0.00 | 0.13 | |
| calculateF | 0.42 | 0.03 | 0.45 | |
| calculateKSAAP | 0.16 | 0.00 | 0.16 | |
| calculateQD_Sm | 2.20 | 0.25 | 2.46 | |
| calculateTC | 2.24 | 0.06 | 2.30 | |
| calculateTC_Sm | 0.39 | 0.05 | 0.44 | |
| corr_plot | 35.50 | 1.88 | 37.47 | |
| enrichfindP | 0.75 | 0.04 | 13.26 | |
| enrichfind_hp | 0.09 | 0.02 | 1.16 | |
| enrichplot | 0.38 | 0.01 | 0.39 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.01 | 0.02 | 2.14 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.02 | 0.00 | 0.02 | |
| plotPPI | 0.04 | 0.02 | 0.15 | |
| pred_ensembel | 14.57 | 0.26 | 13.78 | |
| var_imp | 35.25 | 1.31 | 36.58 | |