Matineh Rahmatbakhsh
| Snapshot Date: 2025-08-14 13:45 -0400 (Thu, 14 Aug 2025) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: b0c624c |
| git_last_commit_date: 2025-04-15 12:38:30 -0400 (Tue, 15 Apr 2025) |
| Back to Multiple platform build/check report for BioC 3.22: simplified long |
|
This page was generated on 2025-08-15 12:06 -0400 (Fri, 15 Aug 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4818 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.5.1 (2025-06-13 ucrt) -- "Great Square Root" | 4554 |
| lconway | macOS 12.7.1 Monterey | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4595 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4537 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.5.0 (2025-04-11) -- "How About a Twenty-Six" | 4535 |
| Click on any hostname to see more info about the system (e.g. compilers) (*) as reported by 'uname -p', except on Windows and Mac OS X | ||||
| Package 987/2317 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.15.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| lconway | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.15.0 |
| Command: F:\biocbuild\bbs-3.22-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.22-bioc\R\library --no-vignettes --timings HPiP_1.15.0.tar.gz |
| StartedAt: 2025-08-15 04:12:19 -0400 (Fri, 15 Aug 2025) |
| EndedAt: 2025-08-15 04:19:05 -0400 (Fri, 15 Aug 2025) |
| EllapsedTime: 406.7 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.22-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.22-bioc\R\library --no-vignettes --timings HPiP_1.15.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.22-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 '1.15.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
var_imp 36.14 1.57 37.81
FSmethod 34.87 1.89 36.97
corr_plot 34.95 1.77 36.73
pred_ensembel 13.50 0.47 14.15
enrichfindP 0.63 0.12 13.83
* 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
'F:/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.22-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.22-bioc/R/library' * installing *source* package 'HPiP' ... ** this is package 'HPiP' version '1.15.0' ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.5.1 (2025-06-13 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 98.088264
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 95.295848
iter 10 value 90.369269
iter 20 value 89.575007
iter 30 value 88.993590
iter 40 value 88.968861
iter 50 value 88.968777
final value 88.968765
converged
Fitting Repeat 3
# weights: 103
initial value 97.438282
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.490735
final value 93.810010
converged
Fitting Repeat 5
# weights: 103
initial value 95.293505
iter 10 value 93.847410
final value 93.836068
converged
Fitting Repeat 1
# weights: 305
initial value 129.600932
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 102.090849
iter 10 value 93.836196
final value 93.836066
converged
Fitting Repeat 3
# weights: 305
initial value 98.388836
iter 10 value 94.053794
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 116.108790
final value 93.836066
converged
Fitting Repeat 5
# weights: 305
initial value 113.383428
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 101.956911
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 109.195376
final value 93.903448
converged
Fitting Repeat 3
# weights: 507
initial value 110.815799
iter 10 value 94.037174
iter 20 value 94.035090
final value 94.035088
converged
Fitting Repeat 4
# weights: 507
initial value 111.558107
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 96.391728
final value 93.812866
converged
Fitting Repeat 1
# weights: 103
initial value 104.988383
iter 10 value 94.072157
iter 20 value 93.932723
iter 30 value 93.891373
iter 40 value 92.183481
iter 50 value 85.910512
iter 60 value 85.687957
iter 70 value 84.466035
iter 80 value 84.305057
iter 90 value 83.993812
iter 100 value 82.858117
final value 82.858117
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 105.022090
iter 10 value 94.055940
iter 20 value 85.781747
iter 30 value 84.591829
iter 40 value 83.774094
iter 50 value 83.255491
iter 60 value 83.227070
final value 83.227059
converged
Fitting Repeat 3
# weights: 103
initial value 97.488056
iter 10 value 94.057889
iter 20 value 93.994978
iter 30 value 93.911120
iter 40 value 93.896351
iter 50 value 93.851374
iter 60 value 89.080214
iter 70 value 87.126935
iter 80 value 86.015690
iter 90 value 84.295440
iter 100 value 83.746404
final value 83.746404
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 107.189462
iter 10 value 93.451324
iter 20 value 86.961206
iter 30 value 86.563153
iter 40 value 86.556180
iter 50 value 85.673346
iter 60 value 85.211430
iter 70 value 85.034605
iter 80 value 83.028312
iter 90 value 82.914391
iter 100 value 82.838713
final value 82.838713
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 100.961845
iter 10 value 94.080537
iter 20 value 93.958348
iter 30 value 93.840821
iter 40 value 93.840338
final value 93.840336
converged
Fitting Repeat 1
# weights: 305
initial value 114.707322
iter 10 value 90.127752
iter 20 value 85.781974
iter 30 value 84.148870
iter 40 value 83.347767
iter 50 value 83.087330
iter 60 value 82.009047
iter 70 value 81.671200
iter 80 value 81.616420
iter 90 value 81.532341
iter 100 value 81.477491
final value 81.477491
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.465594
iter 10 value 93.780093
iter 20 value 89.979707
iter 30 value 86.747520
iter 40 value 86.659690
iter 50 value 84.422146
iter 60 value 83.242670
iter 70 value 82.787596
iter 80 value 82.711403
iter 90 value 82.589227
iter 100 value 82.514755
final value 82.514755
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 114.551649
iter 10 value 88.217143
iter 20 value 84.801652
iter 30 value 84.447161
iter 40 value 83.999495
iter 50 value 83.249083
iter 60 value 82.863041
iter 70 value 82.805869
iter 80 value 82.790475
iter 90 value 82.544411
iter 100 value 81.848549
final value 81.848549
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 113.803423
iter 10 value 94.064513
iter 20 value 93.881058
iter 30 value 93.763807
iter 40 value 85.023657
iter 50 value 84.586659
iter 60 value 84.212181
iter 70 value 83.667657
iter 80 value 82.727582
iter 90 value 81.914079
iter 100 value 81.269558
final value 81.269558
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.085905
iter 10 value 95.140579
iter 20 value 94.161125
iter 30 value 85.418537
iter 40 value 84.207055
iter 50 value 82.907175
iter 60 value 81.887755
iter 70 value 81.657590
iter 80 value 81.560770
iter 90 value 81.499412
iter 100 value 81.404930
final value 81.404930
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 111.072852
iter 10 value 94.151329
iter 20 value 93.208855
iter 30 value 91.204987
iter 40 value 87.788414
iter 50 value 85.204026
iter 60 value 83.459186
iter 70 value 82.055175
iter 80 value 81.559551
iter 90 value 81.124994
iter 100 value 80.880034
final value 80.880034
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.253813
iter 10 value 94.241984
iter 20 value 88.477395
iter 30 value 84.938081
iter 40 value 84.389341
iter 50 value 83.275090
iter 60 value 82.636558
iter 70 value 81.985983
iter 80 value 81.265428
iter 90 value 80.978471
iter 100 value 80.579570
final value 80.579570
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 107.351481
iter 10 value 95.946760
iter 20 value 87.750484
iter 30 value 83.471552
iter 40 value 82.384198
iter 50 value 81.900884
iter 60 value 81.631153
iter 70 value 81.473697
iter 80 value 81.379904
iter 90 value 81.278595
iter 100 value 81.165544
final value 81.165544
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.842404
iter 10 value 94.225815
iter 20 value 93.917161
iter 30 value 93.513632
iter 40 value 86.042128
iter 50 value 84.795030
iter 60 value 84.596470
iter 70 value 84.529654
iter 80 value 83.576468
iter 90 value 82.953900
iter 100 value 82.197902
final value 82.197902
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.240814
iter 10 value 92.791104
iter 20 value 86.988772
iter 30 value 86.107731
iter 40 value 85.571114
iter 50 value 85.222096
iter 60 value 84.804876
iter 70 value 83.429600
iter 80 value 83.100367
iter 90 value 82.903889
iter 100 value 82.028368
final value 82.028368
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.365623
final value 93.837715
converged
Fitting Repeat 2
# weights: 103
initial value 94.923691
final value 94.054567
converged
Fitting Repeat 3
# weights: 103
initial value 100.794677
iter 10 value 93.092982
iter 20 value 93.092326
final value 93.092307
converged
Fitting Repeat 4
# weights: 103
initial value 101.315911
iter 10 value 93.837884
iter 20 value 93.836721
iter 30 value 93.656013
iter 40 value 86.643822
final value 86.643770
converged
Fitting Repeat 5
# weights: 103
initial value 116.741273
final value 94.054811
converged
Fitting Repeat 1
# weights: 305
initial value 105.881335
iter 10 value 94.058408
iter 20 value 94.052937
iter 30 value 86.740638
iter 40 value 85.106781
iter 50 value 85.103258
iter 60 value 85.102579
iter 70 value 85.097149
final value 85.096022
converged
Fitting Repeat 2
# weights: 305
initial value 100.693845
iter 10 value 94.056859
iter 20 value 94.052916
iter 30 value 92.159225
iter 40 value 88.612035
iter 50 value 88.603007
iter 60 value 88.562972
iter 70 value 88.561991
iter 80 value 88.558554
iter 90 value 85.045275
iter 100 value 84.014331
final value 84.014331
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 95.178314
iter 10 value 94.007740
iter 20 value 93.960201
iter 30 value 93.935795
iter 40 value 90.109589
iter 50 value 87.299573
iter 60 value 87.299006
iter 70 value 85.663030
iter 80 value 83.820736
iter 90 value 83.705004
final value 83.704739
converged
Fitting Repeat 4
# weights: 305
initial value 102.269170
iter 10 value 94.057730
iter 20 value 93.704818
iter 30 value 86.251233
iter 40 value 86.181028
iter 50 value 86.161638
iter 60 value 84.409785
iter 70 value 84.362175
iter 80 value 83.004221
iter 90 value 82.922616
iter 100 value 82.921832
final value 82.921832
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.297599
iter 10 value 88.700109
iter 20 value 87.543883
iter 30 value 86.397802
iter 40 value 86.214615
iter 50 value 86.207978
iter 60 value 86.206458
iter 70 value 86.204141
final value 86.203633
converged
Fitting Repeat 1
# weights: 507
initial value 98.667417
iter 10 value 93.297288
iter 20 value 93.290371
iter 30 value 93.289720
iter 40 value 93.289572
iter 50 value 93.253730
final value 93.238660
converged
Fitting Repeat 2
# weights: 507
initial value 101.425767
iter 10 value 90.325067
iter 20 value 89.122512
iter 30 value 85.034782
iter 40 value 84.884152
iter 50 value 84.263174
iter 60 value 83.411311
iter 70 value 83.375977
iter 80 value 83.373797
iter 90 value 83.211436
iter 100 value 83.161070
final value 83.161070
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.792930
iter 10 value 94.060721
iter 20 value 93.895090
iter 30 value 84.199581
iter 40 value 84.005292
iter 50 value 83.136426
iter 60 value 83.135345
iter 70 value 83.134527
iter 80 value 83.132606
iter 90 value 83.132473
iter 100 value 83.132213
final value 83.132213
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.261305
iter 10 value 93.112686
iter 20 value 93.110820
iter 30 value 93.064399
iter 40 value 93.064196
iter 50 value 93.062812
iter 60 value 92.871256
iter 70 value 86.246870
iter 80 value 83.318262
iter 90 value 82.164528
iter 100 value 80.435494
final value 80.435494
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.724491
iter 10 value 93.843773
iter 20 value 93.767650
iter 30 value 86.772934
iter 40 value 86.306803
iter 50 value 86.305759
final value 86.305621
converged
Fitting Repeat 1
# weights: 103
initial value 106.997719
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.439697
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 103.679719
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 94.754538
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.964133
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 96.210420
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 98.943043
iter 10 value 91.869827
iter 20 value 91.298889
iter 30 value 91.295018
final value 91.294975
converged
Fitting Repeat 3
# weights: 305
initial value 101.612210
final value 94.477594
converged
Fitting Repeat 4
# weights: 305
initial value 101.671735
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 98.338982
iter 10 value 93.599514
iter 20 value 83.017186
iter 30 value 81.555022
iter 40 value 81.418796
final value 81.418264
converged
Fitting Repeat 1
# weights: 507
initial value 99.411465
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 107.859585
final value 94.354396
converged
Fitting Repeat 3
# weights: 507
initial value 105.103157
iter 10 value 92.983918
final value 92.849997
converged
Fitting Repeat 4
# weights: 507
initial value 101.344688
final value 94.354396
converged
Fitting Repeat 5
# weights: 507
initial value 116.233107
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 99.886603
iter 10 value 94.343655
iter 20 value 87.749705
iter 30 value 86.237783
iter 40 value 84.387502
iter 50 value 83.729648
iter 60 value 83.540203
final value 83.512413
converged
Fitting Repeat 2
# weights: 103
initial value 106.691409
iter 10 value 92.643877
iter 20 value 84.719020
iter 30 value 84.030196
iter 40 value 83.903552
iter 50 value 83.586155
iter 60 value 83.092947
iter 70 value 83.088187
iter 70 value 83.088187
iter 70 value 83.088187
final value 83.088187
converged
Fitting Repeat 3
# weights: 103
initial value 98.109715
iter 10 value 94.486851
iter 20 value 90.743046
iter 30 value 86.085005
iter 40 value 83.648433
iter 50 value 82.964074
iter 60 value 82.484669
iter 70 value 82.431913
iter 80 value 82.068570
iter 90 value 81.135603
iter 100 value 80.728027
final value 80.728027
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.487475
iter 10 value 94.491488
iter 20 value 92.950058
iter 30 value 91.801333
iter 40 value 91.224612
iter 50 value 91.204917
iter 60 value 91.191517
iter 70 value 91.189922
iter 80 value 91.164350
iter 90 value 91.094612
iter 100 value 84.951016
final value 84.951016
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 97.749159
iter 10 value 94.569449
iter 20 value 94.488599
iter 30 value 94.219356
iter 40 value 94.104714
iter 50 value 88.409397
iter 60 value 82.626337
iter 70 value 82.370605
iter 80 value 81.984034
iter 90 value 81.304267
iter 100 value 80.905258
final value 80.905258
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 101.832693
iter 10 value 94.328332
iter 20 value 90.752438
iter 30 value 83.844550
iter 40 value 82.528431
iter 50 value 80.870197
iter 60 value 80.076302
iter 70 value 79.197945
iter 80 value 79.144823
iter 90 value 78.979628
iter 100 value 78.907372
final value 78.907372
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.389784
iter 10 value 94.424820
iter 20 value 85.323401
iter 30 value 84.573785
iter 40 value 83.942702
iter 50 value 82.487336
iter 60 value 80.238612
iter 70 value 79.884616
iter 80 value 79.528220
iter 90 value 79.049332
iter 100 value 78.949641
final value 78.949641
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.493168
iter 10 value 94.485866
iter 20 value 91.232932
iter 30 value 87.318283
iter 40 value 85.128276
iter 50 value 82.743639
iter 60 value 82.139851
iter 70 value 80.505720
iter 80 value 80.138339
iter 90 value 79.992777
iter 100 value 79.865698
final value 79.865698
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.922633
iter 10 value 94.566589
iter 20 value 83.504453
iter 30 value 82.150015
iter 40 value 81.812902
iter 50 value 81.092910
iter 60 value 80.780021
iter 70 value 80.122572
iter 80 value 79.615748
iter 90 value 79.484758
iter 100 value 79.426974
final value 79.426974
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 121.973093
iter 10 value 91.091440
iter 20 value 86.717077
iter 30 value 85.116752
iter 40 value 81.061380
iter 50 value 80.516635
iter 60 value 80.196994
iter 70 value 80.105338
iter 80 value 79.984046
iter 90 value 79.324505
iter 100 value 78.989065
final value 78.989065
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.793030
iter 10 value 94.677417
iter 20 value 94.246702
iter 30 value 86.742114
iter 40 value 81.741721
iter 50 value 80.943072
iter 60 value 80.350076
iter 70 value 79.950271
iter 80 value 79.734585
iter 90 value 79.360176
iter 100 value 78.983416
final value 78.983416
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.296593
iter 10 value 91.198041
iter 20 value 87.178711
iter 30 value 84.373676
iter 40 value 83.991350
iter 50 value 83.780563
iter 60 value 83.589671
iter 70 value 83.224588
iter 80 value 83.163288
iter 90 value 83.126270
iter 100 value 82.880315
final value 82.880315
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 119.119521
iter 10 value 94.532272
iter 20 value 92.294435
iter 30 value 82.910383
iter 40 value 81.319547
iter 50 value 81.047833
iter 60 value 80.213776
iter 70 value 79.991993
iter 80 value 79.661497
iter 90 value 79.314451
iter 100 value 78.915604
final value 78.915604
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 113.117130
iter 10 value 94.309004
iter 20 value 87.286104
iter 30 value 82.177200
iter 40 value 80.563864
iter 50 value 79.994846
iter 60 value 79.617544
iter 70 value 79.313102
iter 80 value 79.065351
iter 90 value 78.949391
iter 100 value 78.894297
final value 78.894297
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.540903
iter 10 value 93.371389
iter 20 value 84.023388
iter 30 value 83.577121
iter 40 value 83.273666
iter 50 value 81.921505
iter 60 value 81.009607
iter 70 value 80.864529
iter 80 value 80.724662
iter 90 value 80.579789
iter 100 value 80.216963
final value 80.216963
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.791416
final value 94.485864
converged
Fitting Repeat 2
# weights: 103
initial value 104.017226
final value 94.485704
converged
Fitting Repeat 3
# weights: 103
initial value 107.621368
final value 94.485644
converged
Fitting Repeat 4
# weights: 103
initial value 101.542877
final value 94.486027
converged
Fitting Repeat 5
# weights: 103
initial value 96.487820
final value 94.486034
converged
Fitting Repeat 1
# weights: 305
initial value 115.410170
iter 10 value 94.489411
iter 20 value 94.483652
iter 30 value 84.635063
iter 40 value 84.379501
final value 84.281317
converged
Fitting Repeat 2
# weights: 305
initial value 107.502562
iter 10 value 94.489166
iter 20 value 85.656422
iter 30 value 85.652398
iter 40 value 85.247718
final value 85.247483
converged
Fitting Repeat 3
# weights: 305
initial value 101.212311
iter 10 value 94.349701
iter 20 value 94.346670
final value 94.345858
converged
Fitting Repeat 4
# weights: 305
initial value 108.881549
iter 10 value 94.503153
iter 20 value 94.497326
iter 30 value 92.550225
iter 40 value 91.539998
iter 50 value 91.536098
iter 60 value 91.528156
iter 70 value 90.007435
iter 80 value 80.780209
iter 90 value 80.754678
iter 100 value 80.746576
final value 80.746576
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.230225
iter 10 value 94.489145
iter 20 value 94.370092
iter 30 value 86.129785
iter 40 value 85.999145
iter 50 value 85.192317
iter 60 value 84.321023
iter 70 value 83.759202
iter 80 value 83.555903
iter 90 value 83.255807
iter 100 value 83.254441
final value 83.254441
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 100.279998
iter 10 value 94.485439
iter 20 value 94.117444
iter 30 value 92.369417
iter 40 value 90.547737
iter 50 value 90.531165
iter 60 value 90.530115
final value 90.529363
converged
Fitting Repeat 2
# weights: 507
initial value 98.165135
iter 10 value 94.492316
iter 20 value 94.337476
iter 30 value 87.886145
iter 40 value 82.651177
iter 50 value 82.362736
final value 82.306492
converged
Fitting Repeat 3
# weights: 507
initial value 112.422522
iter 10 value 88.823923
iter 20 value 84.394447
iter 30 value 84.264560
iter 40 value 83.269427
iter 50 value 83.258939
final value 83.253926
converged
Fitting Repeat 4
# weights: 507
initial value 117.468126
iter 10 value 94.362381
iter 20 value 94.107203
iter 30 value 84.453225
iter 40 value 83.045942
iter 50 value 81.998138
iter 60 value 81.200252
iter 70 value 80.232724
iter 80 value 79.827973
iter 90 value 79.482192
iter 100 value 78.100131
final value 78.100131
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.881663
iter 10 value 94.362979
iter 20 value 94.355259
final value 94.345708
converged
Fitting Repeat 1
# weights: 103
initial value 96.616200
final value 93.836066
converged
Fitting Repeat 2
# weights: 103
initial value 100.994266
iter 10 value 93.836066
iter 10 value 93.836066
iter 10 value 93.836066
final value 93.836066
converged
Fitting Repeat 3
# weights: 103
initial value 98.164925
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 96.831187
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 95.889708
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 98.109379
final value 93.836066
converged
Fitting Repeat 2
# weights: 305
initial value 101.773707
final value 94.052911
converged
Fitting Repeat 3
# weights: 305
initial value 106.190223
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 114.220503
iter 10 value 93.836078
final value 93.836066
converged
Fitting Repeat 5
# weights: 305
initial value 96.112631
iter 10 value 89.772367
final value 89.757988
converged
Fitting Repeat 1
# weights: 507
initial value 114.244308
final value 93.836066
converged
Fitting Repeat 2
# weights: 507
initial value 102.107885
iter 10 value 93.895409
iter 20 value 93.771264
iter 30 value 91.614821
iter 40 value 90.482658
iter 50 value 90.470761
iter 60 value 90.468556
final value 90.468542
converged
Fitting Repeat 3
# weights: 507
initial value 97.056652
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 100.021031
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 105.290433
iter 10 value 93.293794
iter 20 value 91.034864
iter 30 value 87.976329
iter 40 value 87.825196
iter 50 value 87.791414
final value 87.791333
converged
Fitting Repeat 1
# weights: 103
initial value 112.871512
iter 10 value 93.854006
iter 20 value 88.673345
iter 30 value 85.741865
iter 40 value 84.835211
iter 50 value 84.337300
iter 60 value 84.201240
final value 84.186105
converged
Fitting Repeat 2
# weights: 103
initial value 100.650235
iter 10 value 94.055743
iter 20 value 94.002814
iter 30 value 93.902773
iter 40 value 93.879509
iter 50 value 93.871596
iter 60 value 86.967172
iter 70 value 82.862696
iter 80 value 82.538910
iter 90 value 81.810871
iter 100 value 79.238338
final value 79.238338
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 95.509869
iter 10 value 93.316368
iter 20 value 87.197124
iter 30 value 84.528948
iter 40 value 79.977302
iter 50 value 79.337180
iter 60 value 78.985534
iter 70 value 78.983933
iter 80 value 78.982958
iter 90 value 78.940959
iter 100 value 78.912365
final value 78.912365
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 104.052367
iter 10 value 93.999672
iter 20 value 92.197785
iter 30 value 86.014236
iter 40 value 85.158825
iter 50 value 84.742713
iter 60 value 80.284674
iter 70 value 79.229432
iter 80 value 78.874496
iter 90 value 78.768359
iter 100 value 78.717436
final value 78.717436
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 108.254658
iter 10 value 92.914974
iter 20 value 84.461716
iter 30 value 83.887930
iter 40 value 83.719461
iter 50 value 83.710302
iter 50 value 83.710301
iter 50 value 83.710301
final value 83.710301
converged
Fitting Repeat 1
# weights: 305
initial value 110.129276
iter 10 value 94.047925
iter 20 value 88.414057
iter 30 value 87.614871
iter 40 value 82.280679
iter 50 value 80.634925
iter 60 value 80.196469
iter 70 value 79.898880
iter 80 value 79.870818
iter 90 value 79.691723
iter 100 value 78.505614
final value 78.505614
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 120.436070
iter 10 value 94.206212
iter 20 value 93.890774
iter 30 value 88.639613
iter 40 value 84.452981
iter 50 value 83.759636
iter 60 value 82.528682
iter 70 value 81.198595
iter 80 value 80.944003
iter 90 value 79.704836
iter 100 value 79.358164
final value 79.358164
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.045450
iter 10 value 94.125624
iter 20 value 87.870581
iter 30 value 85.468553
iter 40 value 83.075515
iter 50 value 82.004552
iter 60 value 81.486814
iter 70 value 80.733252
iter 80 value 80.021721
iter 90 value 79.900883
iter 100 value 79.770548
final value 79.770548
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 116.315057
iter 10 value 93.952584
iter 20 value 88.357923
iter 30 value 82.992499
iter 40 value 79.998988
iter 50 value 79.576282
iter 60 value 79.346042
iter 70 value 78.731888
iter 80 value 78.088266
iter 90 value 77.557222
iter 100 value 77.374684
final value 77.374684
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.994135
iter 10 value 96.593266
iter 20 value 94.170829
iter 30 value 93.527189
iter 40 value 91.037966
iter 50 value 90.083085
iter 60 value 85.200955
iter 70 value 83.681116
iter 80 value 82.378437
iter 90 value 81.350889
iter 100 value 81.137768
final value 81.137768
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 128.251200
iter 10 value 94.064195
iter 20 value 91.618532
iter 30 value 84.663488
iter 40 value 82.827086
iter 50 value 82.134959
iter 60 value 81.825674
iter 70 value 79.383259
iter 80 value 79.134374
iter 90 value 79.079874
iter 100 value 78.762779
final value 78.762779
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 118.572752
iter 10 value 94.150909
iter 20 value 90.605549
iter 30 value 85.008480
iter 40 value 84.358900
iter 50 value 80.769527
iter 60 value 79.653024
iter 70 value 79.274024
iter 80 value 79.083351
iter 90 value 78.932892
iter 100 value 78.796162
final value 78.796162
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.860767
iter 10 value 94.291201
iter 20 value 88.682631
iter 30 value 85.048698
iter 40 value 80.887856
iter 50 value 78.976173
iter 60 value 77.735294
iter 70 value 77.328474
iter 80 value 77.218888
iter 90 value 77.076845
iter 100 value 77.066013
final value 77.066013
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 127.998533
iter 10 value 94.134558
iter 20 value 93.552658
iter 30 value 84.896743
iter 40 value 84.146592
iter 50 value 82.136026
iter 60 value 80.932474
iter 70 value 78.750807
iter 80 value 78.220693
iter 90 value 77.808415
iter 100 value 77.538198
final value 77.538198
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 119.053370
iter 10 value 94.569587
iter 20 value 94.158070
iter 30 value 93.849714
iter 40 value 90.819677
iter 50 value 88.623805
iter 60 value 82.701493
iter 70 value 81.803615
iter 80 value 80.222449
iter 90 value 79.745846
iter 100 value 79.370729
final value 79.370729
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.524145
iter 10 value 93.837676
iter 20 value 93.836598
final value 93.835909
converged
Fitting Repeat 2
# weights: 103
initial value 100.190672
final value 94.054682
converged
Fitting Repeat 3
# weights: 103
initial value 103.409874
iter 10 value 94.053877
final value 94.053295
converged
Fitting Repeat 4
# weights: 103
initial value 109.451359
iter 10 value 93.837602
iter 20 value 93.836715
iter 30 value 93.812810
iter 40 value 86.683250
iter 50 value 84.316265
iter 60 value 82.901297
iter 70 value 82.873273
iter 80 value 82.847648
iter 90 value 82.692376
iter 100 value 82.678303
final value 82.678303
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 95.723466
iter 10 value 93.837834
iter 20 value 93.836743
final value 93.836255
converged
Fitting Repeat 1
# weights: 305
initial value 96.316854
iter 10 value 93.814406
iter 20 value 93.760441
iter 30 value 91.996562
iter 40 value 81.907341
iter 50 value 81.882976
iter 60 value 81.881864
iter 70 value 80.315673
iter 80 value 78.355821
iter 90 value 77.163058
iter 100 value 76.657972
final value 76.657972
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 97.772020
iter 10 value 94.057837
iter 20 value 94.050017
final value 93.836343
converged
Fitting Repeat 3
# weights: 305
initial value 95.363774
iter 10 value 94.057505
iter 20 value 93.965028
final value 93.811247
converged
Fitting Repeat 4
# weights: 305
initial value 110.645915
iter 10 value 94.063862
iter 20 value 94.058497
iter 30 value 93.788183
iter 40 value 86.676624
iter 50 value 86.549446
iter 60 value 86.547674
iter 70 value 86.541868
iter 80 value 86.217660
iter 90 value 84.760981
iter 100 value 76.941303
final value 76.941303
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.525663
iter 10 value 94.057995
iter 20 value 94.052915
iter 20 value 94.052914
final value 94.052914
converged
Fitting Repeat 1
# weights: 507
initial value 124.062866
iter 10 value 93.844484
iter 20 value 93.836985
iter 30 value 93.351283
iter 40 value 84.972384
iter 50 value 84.785052
iter 60 value 84.784189
iter 70 value 84.322147
iter 80 value 82.189411
iter 90 value 80.034618
iter 100 value 79.695403
final value 79.695403
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 114.374364
iter 10 value 93.846473
iter 20 value 93.840742
iter 30 value 92.938186
iter 40 value 83.986731
iter 50 value 83.805941
iter 60 value 83.803122
final value 83.803046
converged
Fitting Repeat 3
# weights: 507
initial value 112.018320
iter 10 value 94.060926
iter 20 value 93.523592
iter 30 value 86.811577
iter 40 value 86.597465
iter 50 value 86.584310
iter 60 value 86.419524
final value 86.419404
converged
Fitting Repeat 4
# weights: 507
initial value 97.032737
iter 10 value 93.847904
iter 20 value 93.798728
iter 30 value 89.298773
iter 40 value 89.289860
iter 50 value 89.175664
iter 60 value 89.135903
iter 70 value 89.017142
final value 89.017135
converged
Fitting Repeat 5
# weights: 507
initial value 100.393344
iter 10 value 93.854770
iter 20 value 93.842863
iter 30 value 93.828337
iter 40 value 93.825500
iter 50 value 88.323474
iter 60 value 82.483280
iter 70 value 78.313385
iter 80 value 77.925654
iter 90 value 77.923381
iter 100 value 77.922740
final value 77.922740
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.523429
iter 10 value 87.042979
final value 87.032769
converged
Fitting Repeat 2
# weights: 103
initial value 101.178210
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.162245
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 99.160082
iter 10 value 91.644165
iter 20 value 91.322388
final value 91.322383
converged
Fitting Repeat 5
# weights: 103
initial value 97.600872
iter 10 value 94.112648
final value 94.112570
converged
Fitting Repeat 1
# weights: 305
initial value 103.139432
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 108.597218
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 100.478959
final value 94.467391
converged
Fitting Repeat 4
# weights: 305
initial value 99.203396
final value 94.467391
converged
Fitting Repeat 5
# weights: 305
initial value 98.755724
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 125.462748
iter 10 value 88.446190
iter 20 value 85.103733
iter 30 value 85.097108
iter 40 value 85.095380
final value 85.095257
converged
Fitting Repeat 2
# weights: 507
initial value 95.577791
iter 10 value 94.066783
iter 10 value 94.066783
iter 10 value 94.066783
final value 94.066783
converged
Fitting Repeat 3
# weights: 507
initial value 100.895707
iter 10 value 94.466856
final value 94.466823
converged
Fitting Repeat 4
# weights: 507
initial value 101.051545
iter 10 value 93.422104
iter 20 value 85.239358
iter 30 value 81.738364
iter 40 value 81.737460
final value 81.737351
converged
Fitting Repeat 5
# weights: 507
initial value 105.087254
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 103.200864
iter 10 value 94.488561
iter 20 value 94.038570
iter 30 value 93.975094
iter 40 value 93.968513
iter 50 value 93.949036
iter 60 value 87.350753
iter 70 value 82.661343
iter 80 value 82.411859
iter 90 value 82.168193
iter 100 value 80.988943
final value 80.988943
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.823127
iter 10 value 93.400538
iter 20 value 83.950412
iter 30 value 82.983122
iter 40 value 82.888105
final value 82.877881
converged
Fitting Repeat 3
# weights: 103
initial value 101.903166
iter 10 value 94.386187
iter 20 value 92.740364
iter 30 value 89.201872
iter 40 value 87.317832
iter 50 value 86.468914
iter 60 value 84.087613
iter 70 value 82.807937
iter 80 value 82.793271
iter 90 value 82.786053
iter 100 value 82.784560
final value 82.784560
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 104.293447
iter 10 value 94.400361
iter 20 value 87.765371
iter 30 value 82.972684
iter 40 value 82.879053
iter 50 value 82.877887
final value 82.877881
converged
Fitting Repeat 5
# weights: 103
initial value 99.054392
iter 10 value 94.625134
iter 20 value 94.488026
iter 30 value 94.369379
iter 40 value 94.119875
iter 50 value 93.979695
iter 60 value 93.949702
iter 70 value 84.524887
iter 80 value 82.510804
iter 90 value 81.931358
iter 100 value 80.810654
final value 80.810654
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 102.120667
iter 10 value 86.893255
iter 20 value 86.441877
iter 30 value 84.789956
iter 40 value 80.806146
iter 50 value 79.702994
iter 60 value 78.809455
iter 70 value 78.597582
iter 80 value 78.584327
iter 90 value 78.578032
iter 100 value 78.533230
final value 78.533230
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.901888
iter 10 value 94.511170
iter 20 value 93.592260
iter 30 value 89.461935
iter 40 value 83.982974
iter 50 value 82.124391
iter 60 value 80.389331
iter 70 value 80.172454
iter 80 value 80.037461
iter 90 value 79.667145
iter 100 value 79.260578
final value 79.260578
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 128.403232
iter 10 value 94.494086
iter 20 value 87.264963
iter 30 value 86.224030
iter 40 value 83.716675
iter 50 value 83.479453
iter 60 value 83.108761
iter 70 value 82.515708
iter 80 value 82.078120
iter 90 value 80.922964
iter 100 value 80.591344
final value 80.591344
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.818990
iter 10 value 94.534773
iter 20 value 91.040301
iter 30 value 83.771142
iter 40 value 83.170617
iter 50 value 83.009283
iter 60 value 82.832689
iter 70 value 81.186717
iter 80 value 80.327012
iter 90 value 79.561819
iter 100 value 78.974533
final value 78.974533
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.064808
iter 10 value 94.499601
iter 20 value 94.312721
iter 30 value 89.808226
iter 40 value 87.062399
iter 50 value 84.571851
iter 60 value 81.598220
iter 70 value 78.902823
iter 80 value 78.689693
iter 90 value 78.566231
iter 100 value 78.435076
final value 78.435076
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.793102
iter 10 value 94.539398
iter 20 value 94.489159
iter 30 value 93.594242
iter 40 value 92.398024
iter 50 value 90.730273
iter 60 value 88.252623
iter 70 value 81.330267
iter 80 value 79.714470
iter 90 value 79.533280
iter 100 value 79.353886
final value 79.353886
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.983222
iter 10 value 94.308136
iter 20 value 83.858900
iter 30 value 83.209539
iter 40 value 82.117941
iter 50 value 80.713249
iter 60 value 79.807122
iter 70 value 79.074901
iter 80 value 78.696940
iter 90 value 78.631647
iter 100 value 78.458363
final value 78.458363
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 116.674418
iter 10 value 95.102500
iter 20 value 94.435325
iter 30 value 93.984650
iter 40 value 89.885160
iter 50 value 87.904971
iter 60 value 87.168311
iter 70 value 84.026916
iter 80 value 83.164393
iter 90 value 82.477214
iter 100 value 81.617787
final value 81.617787
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.887962
iter 10 value 94.928270
iter 20 value 91.626144
iter 30 value 84.248409
iter 40 value 82.065045
iter 50 value 81.615027
iter 60 value 81.242332
iter 70 value 81.004985
iter 80 value 80.764901
iter 90 value 80.118282
iter 100 value 79.718779
final value 79.718779
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.259287
iter 10 value 91.207953
iter 20 value 87.293825
iter 30 value 86.785901
iter 40 value 82.821202
iter 50 value 80.291049
iter 60 value 79.672305
iter 70 value 79.439193
iter 80 value 79.063179
iter 90 value 78.705738
iter 100 value 78.330331
final value 78.330331
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.125510
final value 94.485747
converged
Fitting Repeat 2
# weights: 103
initial value 103.888507
final value 94.485784
converged
Fitting Repeat 3
# weights: 103
initial value 98.276775
final value 94.485916
converged
Fitting Repeat 4
# weights: 103
initial value 102.223198
final value 94.486014
converged
Fitting Repeat 5
# weights: 103
initial value 98.335354
iter 10 value 94.485802
iter 20 value 94.484227
final value 94.484213
converged
Fitting Repeat 1
# weights: 305
initial value 107.006174
iter 10 value 93.408337
iter 20 value 93.396559
iter 30 value 93.392533
iter 40 value 90.981098
iter 50 value 90.552257
iter 60 value 90.177185
iter 70 value 90.057795
final value 90.055405
converged
Fitting Repeat 2
# weights: 305
initial value 102.815648
iter 10 value 94.149346
iter 20 value 90.743073
iter 30 value 86.749013
iter 40 value 83.220353
iter 50 value 81.204161
iter 60 value 81.198635
final value 81.198194
converged
Fitting Repeat 3
# weights: 305
initial value 104.554821
iter 10 value 94.472051
iter 20 value 94.466146
iter 30 value 83.819155
iter 40 value 82.094592
iter 50 value 82.094128
final value 82.093770
converged
Fitting Repeat 4
# weights: 305
initial value 98.648590
iter 10 value 94.489157
iter 20 value 94.464019
iter 30 value 93.826791
iter 40 value 91.459284
iter 50 value 91.395206
iter 60 value 91.090645
iter 70 value 91.083031
final value 91.082966
converged
Fitting Repeat 5
# weights: 305
initial value 108.954634
iter 10 value 94.489477
iter 20 value 94.484422
final value 94.484363
converged
Fitting Repeat 1
# weights: 507
initial value 98.514761
iter 10 value 94.492897
iter 20 value 92.408219
iter 30 value 90.400566
final value 90.386563
converged
Fitting Repeat 2
# weights: 507
initial value 102.250010
iter 10 value 93.875724
iter 20 value 93.433056
iter 30 value 93.430886
iter 40 value 93.426901
iter 50 value 93.423779
iter 60 value 93.197167
iter 70 value 84.044899
iter 80 value 83.872680
iter 90 value 81.601672
iter 100 value 78.973549
final value 78.973549
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 98.746139
iter 10 value 94.467247
iter 20 value 92.123275
iter 30 value 85.158318
iter 40 value 81.459071
iter 50 value 81.420998
iter 60 value 81.414431
iter 70 value 80.278687
iter 80 value 80.050848
iter 90 value 79.955771
iter 100 value 79.952115
final value 79.952115
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 102.143523
iter 10 value 94.363367
iter 20 value 90.424531
iter 30 value 90.398899
iter 40 value 90.291189
iter 50 value 90.231649
iter 60 value 90.231581
final value 90.231569
converged
Fitting Repeat 5
# weights: 507
initial value 110.298602
iter 10 value 94.492799
iter 20 value 94.448429
iter 30 value 94.201625
iter 40 value 94.146329
iter 50 value 94.144234
iter 60 value 94.137259
iter 70 value 94.136235
iter 80 value 94.135871
iter 90 value 94.135583
final value 94.135126
converged
Fitting Repeat 1
# weights: 103
initial value 101.263560
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.948521
final value 94.057229
converged
Fitting Repeat 3
# weights: 103
initial value 95.176448
iter 10 value 93.919416
iter 20 value 93.889023
final value 93.888889
converged
Fitting Repeat 4
# weights: 103
initial value 105.884385
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 100.524764
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.582281
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 97.954506
final value 94.482478
converged
Fitting Repeat 3
# weights: 305
initial value 99.713139
iter 10 value 91.394347
final value 91.321633
converged
Fitting Repeat 4
# weights: 305
initial value 103.148175
iter 10 value 94.558212
iter 20 value 91.104530
iter 30 value 89.277750
iter 40 value 88.113167
iter 50 value 86.621068
iter 60 value 86.446064
iter 70 value 86.440572
iter 80 value 86.391466
final value 86.389501
converged
Fitting Repeat 5
# weights: 305
initial value 103.677930
final value 94.275362
converged
Fitting Repeat 1
# weights: 507
initial value 103.391998
final value 94.275363
converged
Fitting Repeat 2
# weights: 507
initial value 94.833079
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 97.853553
iter 10 value 91.157426
iter 20 value 87.593887
iter 30 value 87.590735
final value 87.590732
converged
Fitting Repeat 4
# weights: 507
initial value 105.858484
final value 94.275362
converged
Fitting Repeat 5
# weights: 507
initial value 96.008548
iter 10 value 94.275363
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 1
# weights: 103
initial value 98.235401
iter 10 value 94.501232
iter 20 value 94.425019
iter 30 value 93.970146
iter 40 value 92.409183
iter 50 value 88.641504
iter 60 value 88.575483
iter 70 value 88.574304
iter 80 value 88.537364
iter 90 value 88.381765
iter 100 value 85.857694
final value 85.857694
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 108.388261
iter 10 value 87.472617
iter 20 value 86.404565
iter 30 value 85.526699
iter 40 value 85.506787
final value 85.505404
converged
Fitting Repeat 3
# weights: 103
initial value 100.054839
iter 10 value 94.242774
iter 20 value 88.658982
iter 30 value 88.383088
iter 40 value 88.294167
iter 50 value 88.244048
iter 60 value 85.713815
iter 70 value 85.420127
final value 85.411355
converged
Fitting Repeat 4
# weights: 103
initial value 97.636082
iter 10 value 94.518378
iter 20 value 94.134326
iter 30 value 89.498588
iter 40 value 88.860783
iter 50 value 86.233259
iter 60 value 85.982667
iter 70 value 85.718744
iter 80 value 85.620839
iter 90 value 85.465640
iter 100 value 85.411440
final value 85.411440
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 97.409152
iter 10 value 94.491254
iter 20 value 94.486652
iter 30 value 90.216014
iter 40 value 86.050206
iter 50 value 85.930196
iter 60 value 85.873820
iter 70 value 85.692883
iter 80 value 85.518619
iter 90 value 85.412116
final value 85.411355
converged
Fitting Repeat 1
# weights: 305
initial value 102.248536
iter 10 value 94.421482
iter 20 value 92.698635
iter 30 value 91.678485
iter 40 value 87.868089
iter 50 value 86.914722
iter 60 value 86.011792
iter 70 value 84.597616
iter 80 value 84.362858
iter 90 value 84.149248
iter 100 value 84.033986
final value 84.033986
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 134.465946
iter 10 value 94.473092
iter 20 value 88.444680
iter 30 value 86.519369
iter 40 value 85.985600
iter 50 value 85.857058
iter 60 value 85.264013
iter 70 value 84.264005
iter 80 value 83.897914
iter 90 value 83.707634
iter 100 value 83.651875
final value 83.651875
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.194706
iter 10 value 94.221084
iter 20 value 88.600247
iter 30 value 87.610030
iter 40 value 85.699633
iter 50 value 84.991656
iter 60 value 84.096624
iter 70 value 83.274577
iter 80 value 83.001739
iter 90 value 82.867390
iter 100 value 82.758847
final value 82.758847
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.125704
iter 10 value 91.540187
iter 20 value 87.299827
iter 30 value 84.931634
iter 40 value 83.974439
iter 50 value 83.465207
iter 60 value 82.970605
iter 70 value 82.748953
iter 80 value 82.668098
iter 90 value 82.654824
iter 100 value 82.643910
final value 82.643910
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 113.099762
iter 10 value 94.326439
iter 20 value 88.403495
iter 30 value 87.734708
iter 40 value 87.291114
iter 50 value 86.068122
iter 60 value 85.406941
iter 70 value 84.125995
iter 80 value 83.719008
iter 90 value 83.123454
iter 100 value 82.833052
final value 82.833052
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.927447
iter 10 value 94.692598
iter 20 value 93.645281
iter 30 value 87.408057
iter 40 value 85.928778
iter 50 value 85.078918
iter 60 value 83.628566
iter 70 value 82.889316
iter 80 value 82.763718
iter 90 value 82.516964
iter 100 value 82.376356
final value 82.376356
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.612922
iter 10 value 94.669854
iter 20 value 89.447389
iter 30 value 86.686390
iter 40 value 85.774226
iter 50 value 85.642537
iter 60 value 84.893830
iter 70 value 84.136677
iter 80 value 82.983093
iter 90 value 82.687444
iter 100 value 82.634372
final value 82.634372
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 124.794176
iter 10 value 95.323591
iter 20 value 87.673324
iter 30 value 85.670101
iter 40 value 85.058208
iter 50 value 84.095491
iter 60 value 83.517277
iter 70 value 83.081934
iter 80 value 83.036230
iter 90 value 82.912724
iter 100 value 82.857928
final value 82.857928
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 122.355149
iter 10 value 94.375466
iter 20 value 88.705139
iter 30 value 88.276970
iter 40 value 86.915540
iter 50 value 85.865223
iter 60 value 85.572941
iter 70 value 85.181848
iter 80 value 83.969158
iter 90 value 83.527631
iter 100 value 83.394734
final value 83.394734
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 111.034935
iter 10 value 94.493395
iter 20 value 84.834867
iter 30 value 83.846745
iter 40 value 83.396847
iter 50 value 83.251538
iter 60 value 83.029881
iter 70 value 82.784543
iter 80 value 82.615151
iter 90 value 82.512934
iter 100 value 82.312781
final value 82.312781
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.415500
final value 94.486003
converged
Fitting Repeat 2
# weights: 103
initial value 103.011586
iter 10 value 93.947687
iter 20 value 93.924117
iter 30 value 93.923640
iter 40 value 93.923219
iter 50 value 93.865829
final value 93.865183
converged
Fitting Repeat 3
# weights: 103
initial value 96.007296
iter 10 value 94.485803
final value 94.484248
converged
Fitting Repeat 4
# weights: 103
initial value 96.704380
final value 94.485787
converged
Fitting Repeat 5
# weights: 103
initial value 101.958599
final value 94.058913
converged
Fitting Repeat 1
# weights: 305
initial value 105.142434
iter 10 value 94.488715
iter 20 value 94.475442
iter 30 value 94.326468
final value 94.326392
converged
Fitting Repeat 2
# weights: 305
initial value 121.248254
iter 10 value 94.489532
iter 20 value 94.314381
iter 30 value 91.019486
iter 40 value 86.438590
iter 50 value 86.275649
iter 60 value 86.275393
final value 86.274971
converged
Fitting Repeat 3
# weights: 305
initial value 96.667962
iter 10 value 92.942095
iter 20 value 92.797768
iter 30 value 92.795983
iter 40 value 92.791240
iter 50 value 91.690975
iter 60 value 87.429033
iter 70 value 87.189062
iter 80 value 87.176359
final value 87.152893
converged
Fitting Repeat 4
# weights: 305
initial value 99.313858
iter 10 value 94.489491
iter 20 value 94.485071
iter 30 value 87.099887
iter 40 value 86.549918
iter 50 value 86.287789
iter 60 value 86.258845
iter 70 value 86.257788
iter 80 value 86.218042
iter 90 value 86.217241
iter 100 value 86.216985
final value 86.216985
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 97.141391
iter 10 value 94.280466
iter 20 value 94.275914
final value 94.275642
converged
Fitting Repeat 1
# weights: 507
initial value 109.690679
iter 10 value 94.491951
iter 20 value 94.484681
iter 30 value 94.410259
iter 40 value 91.230910
iter 50 value 86.550581
iter 60 value 86.503532
iter 70 value 86.500090
iter 80 value 84.717584
iter 90 value 84.697395
iter 100 value 84.691828
final value 84.691828
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 96.163610
iter 10 value 94.283403
iter 20 value 93.598667
iter 30 value 86.928167
iter 40 value 85.063248
final value 85.063229
converged
Fitting Repeat 3
# weights: 507
initial value 114.714186
iter 10 value 94.283419
iter 20 value 94.276459
final value 94.276390
converged
Fitting Repeat 4
# weights: 507
initial value 107.712369
iter 10 value 94.283597
iter 20 value 94.277380
iter 30 value 93.643893
iter 40 value 90.799201
iter 50 value 89.337238
iter 60 value 89.335807
iter 70 value 89.335441
iter 80 value 89.333261
iter 90 value 88.117569
iter 100 value 87.757439
final value 87.757439
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 111.772577
iter 10 value 94.492352
iter 20 value 94.459696
iter 30 value 93.201996
iter 40 value 85.966151
iter 50 value 85.907491
iter 60 value 83.766426
iter 70 value 83.291247
iter 80 value 83.289101
iter 90 value 83.274465
iter 100 value 82.659111
final value 82.659111
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 134.046290
iter 10 value 117.708829
iter 20 value 115.009785
iter 30 value 107.939393
iter 40 value 105.467931
iter 50 value 104.508672
iter 60 value 102.383467
iter 70 value 102.081166
iter 80 value 101.774923
iter 90 value 101.076127
iter 100 value 100.770931
final value 100.770931
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 153.002508
iter 10 value 119.776868
iter 20 value 112.397503
iter 30 value 110.912461
iter 40 value 109.281833
iter 50 value 108.933500
iter 60 value 106.088621
iter 70 value 103.190941
iter 80 value 102.280976
iter 90 value 101.979430
iter 100 value 101.359512
final value 101.359512
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 143.580644
iter 10 value 116.754729
iter 20 value 111.509118
iter 30 value 110.055578
iter 40 value 106.146968
iter 50 value 104.709791
iter 60 value 104.382857
iter 70 value 104.332732
iter 80 value 104.271475
iter 90 value 103.466736
iter 100 value 102.000566
final value 102.000566
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 129.877437
iter 10 value 118.087261
iter 20 value 112.127587
iter 30 value 110.583561
iter 40 value 109.573695
iter 50 value 106.878741
iter 60 value 105.147922
iter 70 value 104.338742
iter 80 value 103.066477
iter 90 value 101.662261
iter 100 value 101.117877
final value 101.117877
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 128.413780
iter 10 value 117.899440
iter 20 value 115.020802
iter 30 value 106.533150
iter 40 value 106.225906
iter 50 value 105.881224
iter 60 value 105.310575
iter 70 value 104.849578
iter 80 value 104.360516
iter 90 value 103.141663
iter 100 value 102.706927
final value 102.706927
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 -- Fri Aug 15 04:18:55 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
45.12 1.45 141.70
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 34.87 | 1.89 | 36.97 | |
| FreqInteractors | 0.26 | 0.01 | 0.29 | |
| calculateAAC | 0.00 | 0.07 | 0.06 | |
| calculateAutocor | 0.53 | 0.11 | 0.64 | |
| calculateCTDC | 0.11 | 0.01 | 0.13 | |
| calculateCTDD | 0.81 | 0.06 | 0.87 | |
| calculateCTDT | 0.31 | 0.02 | 0.33 | |
| calculateCTriad | 0.50 | 0.01 | 0.52 | |
| calculateDC | 0.10 | 0.00 | 0.09 | |
| calculateF | 0.42 | 0.05 | 0.47 | |
| calculateKSAAP | 0.14 | 0.02 | 0.15 | |
| calculateQD_Sm | 2.31 | 0.11 | 2.43 | |
| calculateTC | 2.03 | 0.12 | 2.15 | |
| calculateTC_Sm | 0.30 | 0.08 | 0.38 | |
| corr_plot | 34.95 | 1.77 | 36.73 | |
| enrichfindP | 0.63 | 0.12 | 13.83 | |
| enrichfind_hp | 0.29 | 0.02 | 1.61 | |
| enrichplot | 0.32 | 0.00 | 0.37 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.01 | 0.00 | 2.24 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.00 | 0.01 | 0.01 | |
| plotPPI | 0.06 | 0.02 | 0.16 | |
| pred_ensembel | 13.50 | 0.47 | 14.15 | |
| var_imp | 36.14 | 1.57 | 37.81 | |