Matineh Rahmatbakhsh
| Snapshot Date: 2026-03-15 13:40 -0400 (Sun, 15 Mar 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: 68bd9a1 |
| git_last_commit_date: 2025-12-28 18:34:02 -0400 (Sun, 28 Dec 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-03-16 11:34 -0400 (Mon, 16 Mar 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences" | 4837 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2026-03-01 r89506) -- "Unsuffered Consequences" | 4053 |
| 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 1009/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.17.2 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| See other builds for HPiP in R Universe. | ||||||||||||||
|
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: 1.17.2 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.2.tar.gz |
| StartedAt: 2026-03-16 01:13:23 -0400 (Mon, 16 Mar 2026) |
| EndedAt: 2026-03-16 01:28:16 -0400 (Mon, 16 Mar 2026) |
| EllapsedTime: 893.6 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.2.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-03-05 r89546)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-03-16 05:13:23 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... 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
corr_plot 36.721 0.421 37.909
var_imp 33.646 0.486 34.135
FSmethod 32.782 0.572 33.356
pred_ensembel 12.607 0.102 11.430
enrichfindP 0.520 0.047 11.642
* 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 re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.17.2’ ** 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 Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
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 108.431631
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 109.536737
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 102.256521
final value 94.354286
converged
Fitting Repeat 4
# weights: 103
initial value 98.370473
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 102.426419
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 106.936151
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 95.340436
iter 10 value 94.165117
iter 10 value 94.165117
iter 10 value 94.165117
final value 94.165117
converged
Fitting Repeat 3
# weights: 305
initial value 102.366480
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 95.727074
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 102.063865
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 99.306429
iter 10 value 93.315627
iter 20 value 90.921587
final value 90.269739
converged
Fitting Repeat 2
# weights: 507
initial value 106.832174
final value 94.026542
converged
Fitting Repeat 3
# weights: 507
initial value 95.308251
iter 10 value 93.976346
final value 93.976245
converged
Fitting Repeat 4
# weights: 507
initial value 105.584815
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 100.096309
final value 94.026542
converged
Fitting Repeat 1
# weights: 103
initial value 97.488031
iter 10 value 94.484637
iter 20 value 91.607207
iter 30 value 90.500302
iter 40 value 87.630762
iter 50 value 85.596867
iter 60 value 84.857085
iter 70 value 84.339530
iter 80 value 83.792634
iter 90 value 83.702752
iter 100 value 83.682949
final value 83.682949
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 106.643007
iter 10 value 93.799734
iter 20 value 91.616952
iter 30 value 88.881901
iter 40 value 87.732102
iter 50 value 86.558710
iter 60 value 85.841538
iter 70 value 84.994569
iter 80 value 84.581900
iter 90 value 83.918178
iter 100 value 83.657524
final value 83.657524
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.050942
iter 10 value 94.477814
iter 20 value 94.246558
iter 30 value 94.133979
iter 40 value 93.308306
iter 50 value 89.681026
iter 60 value 88.031134
iter 70 value 87.660416
iter 80 value 84.664899
iter 90 value 83.900135
iter 100 value 83.463133
final value 83.463133
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 99.281406
iter 10 value 94.136517
iter 20 value 94.027566
iter 30 value 88.506467
iter 40 value 87.670750
iter 50 value 87.475584
iter 60 value 86.730773
iter 70 value 86.084400
iter 80 value 85.800206
final value 85.790559
converged
Fitting Repeat 5
# weights: 103
initial value 99.346636
iter 10 value 93.065642
iter 20 value 87.797409
iter 30 value 87.551274
iter 40 value 86.901759
iter 50 value 86.539635
iter 60 value 86.416422
iter 70 value 86.407408
final value 86.406914
converged
Fitting Repeat 1
# weights: 305
initial value 120.263658
iter 10 value 94.351353
iter 20 value 94.127718
iter 30 value 93.688156
iter 40 value 89.946292
iter 50 value 87.749199
iter 60 value 85.179448
iter 70 value 83.289184
iter 80 value 82.450019
iter 90 value 82.270762
iter 100 value 82.106775
final value 82.106775
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.163478
iter 10 value 94.422163
iter 20 value 94.092179
iter 30 value 93.274651
iter 40 value 93.195937
iter 50 value 92.272148
iter 60 value 88.718198
iter 70 value 88.393505
iter 80 value 87.469672
iter 90 value 87.239222
iter 100 value 86.962841
final value 86.962841
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.290189
iter 10 value 93.421713
iter 20 value 87.774763
iter 30 value 86.566844
iter 40 value 86.345843
iter 50 value 86.237046
iter 60 value 86.058555
iter 70 value 85.643120
iter 80 value 85.301364
iter 90 value 85.059127
iter 100 value 84.924554
final value 84.924554
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 122.704869
iter 10 value 94.871082
iter 20 value 92.518029
iter 30 value 91.607372
iter 40 value 90.350572
iter 50 value 90.184962
iter 60 value 87.951150
iter 70 value 87.280033
iter 80 value 86.652506
iter 90 value 86.353996
iter 100 value 85.668210
final value 85.668210
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 113.432087
iter 10 value 94.397691
iter 20 value 89.960523
iter 30 value 85.977524
iter 40 value 85.437632
iter 50 value 85.290555
iter 60 value 84.980028
iter 70 value 83.129837
iter 80 value 82.627438
iter 90 value 81.902931
iter 100 value 81.840953
final value 81.840953
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.358079
iter 10 value 94.548348
iter 20 value 93.106802
iter 30 value 90.946414
iter 40 value 87.334000
iter 50 value 86.665387
iter 60 value 86.226063
iter 70 value 85.271341
iter 80 value 84.035254
iter 90 value 82.669350
iter 100 value 82.423365
final value 82.423365
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.818278
iter 10 value 94.596079
iter 20 value 92.047732
iter 30 value 86.993957
iter 40 value 84.337551
iter 50 value 83.164614
iter 60 value 82.852172
iter 70 value 82.675085
iter 80 value 82.468922
iter 90 value 82.330385
iter 100 value 82.194031
final value 82.194031
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 118.517071
iter 10 value 94.270812
iter 20 value 88.947111
iter 30 value 87.920826
iter 40 value 84.908159
iter 50 value 84.362556
iter 60 value 84.243658
iter 70 value 84.157741
iter 80 value 83.586086
iter 90 value 82.817313
iter 100 value 82.369487
final value 82.369487
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.283059
iter 10 value 99.110882
iter 20 value 93.129450
iter 30 value 89.824190
iter 40 value 87.888216
iter 50 value 87.439853
iter 60 value 87.359030
iter 70 value 87.177010
iter 80 value 84.892492
iter 90 value 83.880672
iter 100 value 83.549774
final value 83.549774
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 128.448018
iter 10 value 94.294746
iter 20 value 94.133210
iter 30 value 93.441558
iter 40 value 87.884380
iter 50 value 85.736089
iter 60 value 85.078607
iter 70 value 83.345107
iter 80 value 82.551967
iter 90 value 82.481941
iter 100 value 82.313056
final value 82.313056
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.931666
final value 94.485680
converged
Fitting Repeat 2
# weights: 103
initial value 98.499084
final value 94.485841
converged
Fitting Repeat 3
# weights: 103
initial value 94.684076
final value 94.485894
converged
Fitting Repeat 4
# weights: 103
initial value 105.125052
final value 94.486128
converged
Fitting Repeat 5
# weights: 103
initial value 98.107242
iter 10 value 94.485780
iter 20 value 94.484267
iter 30 value 87.444974
iter 40 value 87.255535
final value 87.255121
converged
Fitting Repeat 1
# weights: 305
initial value 95.707909
iter 10 value 94.485556
final value 94.484239
converged
Fitting Repeat 2
# weights: 305
initial value 115.677578
iter 10 value 94.468001
iter 20 value 93.482398
iter 30 value 87.262812
iter 40 value 87.255472
final value 87.254757
converged
Fitting Repeat 3
# weights: 305
initial value 97.682268
iter 10 value 94.489652
iter 20 value 94.484228
final value 94.484220
converged
Fitting Repeat 4
# weights: 305
initial value 101.593050
iter 10 value 94.170149
iter 20 value 94.106084
iter 30 value 94.026958
iter 40 value 94.026804
iter 40 value 94.026804
iter 50 value 93.975867
iter 60 value 93.974914
final value 93.974913
converged
Fitting Repeat 5
# weights: 305
initial value 122.133292
iter 10 value 94.058342
iter 20 value 93.992555
iter 30 value 93.981559
iter 40 value 93.976409
iter 50 value 88.563473
iter 60 value 87.367642
iter 70 value 87.356584
iter 80 value 87.356226
final value 87.356121
converged
Fitting Repeat 1
# weights: 507
initial value 109.400114
iter 10 value 89.036355
iter 20 value 87.087073
iter 30 value 85.366457
iter 40 value 85.364033
iter 50 value 85.289587
final value 85.284402
converged
Fitting Repeat 2
# weights: 507
initial value 109.212190
iter 10 value 94.456261
iter 20 value 92.811510
iter 30 value 87.359996
iter 40 value 87.254399
iter 50 value 87.196508
final value 87.182434
converged
Fitting Repeat 3
# weights: 507
initial value 119.636565
iter 10 value 94.493575
iter 20 value 94.475915
iter 30 value 94.026857
iter 40 value 92.802860
iter 50 value 89.716538
iter 60 value 89.700914
final value 89.700797
converged
Fitting Repeat 4
# weights: 507
initial value 102.162882
iter 10 value 94.195372
iter 20 value 93.901666
iter 30 value 92.351171
iter 40 value 87.760475
iter 50 value 87.631423
iter 60 value 87.495480
iter 70 value 87.333672
iter 80 value 87.333158
iter 90 value 87.330305
iter 90 value 87.330305
final value 87.330305
converged
Fitting Repeat 5
# weights: 507
initial value 105.769993
iter 10 value 94.173348
iter 20 value 94.168144
iter 30 value 93.975472
iter 30 value 93.975471
iter 30 value 93.975471
final value 93.975471
converged
Fitting Repeat 1
# weights: 103
initial value 96.469219
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 98.646966
final value 94.050051
converged
Fitting Repeat 3
# weights: 103
initial value 105.976250
iter 10 value 94.052910
iter 10 value 94.052910
iter 10 value 94.052910
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 103.138596
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 101.106197
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 123.362561
iter 10 value 93.975224
final value 93.975156
converged
Fitting Repeat 2
# weights: 305
initial value 104.233130
iter 10 value 91.725524
iter 20 value 85.024031
iter 30 value 84.429531
iter 40 value 84.389280
final value 84.389248
converged
Fitting Repeat 3
# weights: 305
initial value 107.899524
final value 94.038251
converged
Fitting Repeat 4
# weights: 305
initial value 112.846760
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 110.954418
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 94.941467
iter 10 value 94.038252
iter 10 value 94.038251
iter 10 value 94.038251
final value 94.038251
converged
Fitting Repeat 2
# weights: 507
initial value 125.311498
iter 10 value 94.688596
iter 20 value 94.038426
final value 94.038251
converged
Fitting Repeat 3
# weights: 507
initial value 128.468125
final value 93.869756
converged
Fitting Repeat 4
# weights: 507
initial value 105.724961
iter 10 value 93.606818
iter 20 value 93.450409
final value 93.450329
converged
Fitting Repeat 5
# weights: 507
initial value 115.834257
final value 94.038251
converged
Fitting Repeat 1
# weights: 103
initial value 100.388998
iter 10 value 94.078616
iter 20 value 86.192175
iter 30 value 84.900700
iter 40 value 84.642773
iter 50 value 83.473938
iter 60 value 83.174620
iter 70 value 83.164356
iter 80 value 83.162799
iter 90 value 83.162361
final value 83.162130
converged
Fitting Repeat 2
# weights: 103
initial value 96.844202
iter 10 value 94.054037
iter 20 value 87.011969
iter 30 value 86.023071
iter 40 value 85.766453
iter 50 value 84.084582
iter 60 value 83.438870
iter 70 value 83.294972
iter 80 value 83.218339
iter 90 value 83.163176
final value 83.162130
converged
Fitting Repeat 3
# weights: 103
initial value 97.152620
iter 10 value 94.057368
iter 20 value 94.000437
iter 30 value 93.641729
iter 40 value 93.609568
iter 50 value 93.567369
iter 60 value 86.489024
iter 70 value 85.778050
iter 80 value 85.733681
iter 90 value 84.457849
iter 100 value 83.289046
final value 83.289046
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.266919
iter 10 value 94.056549
iter 20 value 86.549450
iter 30 value 85.209229
iter 40 value 83.448069
iter 50 value 82.838208
iter 60 value 82.623572
final value 82.622675
converged
Fitting Repeat 5
# weights: 103
initial value 100.890063
iter 10 value 94.133855
iter 20 value 94.055351
iter 30 value 93.920950
iter 40 value 91.153518
iter 50 value 90.891135
iter 60 value 90.806423
iter 70 value 90.771053
final value 90.771012
converged
Fitting Repeat 1
# weights: 305
initial value 129.636599
iter 10 value 94.050712
iter 20 value 86.385916
iter 30 value 85.962063
iter 40 value 85.629513
iter 50 value 84.273295
iter 60 value 80.942158
iter 70 value 79.829502
iter 80 value 79.232263
iter 90 value 79.173346
iter 100 value 79.130775
final value 79.130775
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.310670
iter 10 value 93.987993
iter 20 value 93.011023
iter 30 value 86.209524
iter 40 value 85.109101
iter 50 value 83.370677
iter 60 value 82.963775
iter 70 value 82.939280
iter 80 value 82.846045
iter 90 value 82.205850
iter 100 value 79.935862
final value 79.935862
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.576051
iter 10 value 94.043875
iter 20 value 93.068468
iter 30 value 89.076756
iter 40 value 87.002780
iter 50 value 85.188507
iter 60 value 84.463107
iter 70 value 84.035407
iter 80 value 83.896553
iter 90 value 83.811268
iter 100 value 80.843442
final value 80.843442
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.819383
iter 10 value 94.725396
iter 20 value 91.747116
iter 30 value 90.375740
iter 40 value 84.902431
iter 50 value 84.185299
iter 60 value 82.280109
iter 70 value 81.096669
iter 80 value 80.961798
iter 90 value 80.455455
iter 100 value 79.974705
final value 79.974705
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.468349
iter 10 value 94.051727
iter 20 value 93.675988
iter 30 value 87.661246
iter 40 value 85.931190
iter 50 value 82.507544
iter 60 value 79.452667
iter 70 value 78.728410
iter 80 value 78.525775
iter 90 value 78.423406
iter 100 value 78.363607
final value 78.363607
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.834755
iter 10 value 94.140874
iter 20 value 94.015765
iter 30 value 85.846563
iter 40 value 84.364979
iter 50 value 83.311255
iter 60 value 83.194558
iter 70 value 82.586284
iter 80 value 81.221649
iter 90 value 80.584590
iter 100 value 80.242756
final value 80.242756
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 129.550551
iter 10 value 94.188448
iter 20 value 92.199544
iter 30 value 84.275431
iter 40 value 83.614938
iter 50 value 83.155659
iter 60 value 83.029049
iter 70 value 82.809064
iter 80 value 82.745121
iter 90 value 82.592836
iter 100 value 81.847352
final value 81.847352
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.175491
iter 10 value 94.070622
iter 20 value 86.385220
iter 30 value 83.937830
iter 40 value 83.633827
iter 50 value 83.522997
iter 60 value 83.364895
iter 70 value 83.230036
iter 80 value 82.454525
iter 90 value 80.064836
iter 100 value 78.654594
final value 78.654594
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 124.234968
iter 10 value 94.216139
iter 20 value 92.230481
iter 30 value 85.674747
iter 40 value 83.715800
iter 50 value 83.386401
iter 60 value 83.317214
iter 70 value 82.606230
iter 80 value 80.047390
iter 90 value 79.331505
iter 100 value 79.045325
final value 79.045325
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 118.848355
iter 10 value 93.966556
iter 20 value 93.442224
iter 30 value 84.035066
iter 40 value 82.734662
iter 50 value 82.218986
iter 60 value 80.657957
iter 70 value 80.104868
iter 80 value 79.656725
iter 90 value 79.282625
iter 100 value 79.189245
final value 79.189245
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.540230
final value 94.054518
converged
Fitting Repeat 2
# weights: 103
initial value 97.741737
final value 94.054600
converged
Fitting Repeat 3
# weights: 103
initial value 97.906936
final value 94.054732
converged
Fitting Repeat 4
# weights: 103
initial value 97.230576
iter 10 value 93.765376
iter 20 value 93.620704
final value 93.579877
converged
Fitting Repeat 5
# weights: 103
initial value 95.330448
iter 10 value 94.054532
iter 20 value 93.961027
iter 30 value 88.573752
iter 40 value 80.962722
iter 50 value 80.957827
iter 60 value 80.957251
iter 70 value 80.956306
iter 80 value 80.955873
final value 80.953998
converged
Fitting Repeat 1
# weights: 305
initial value 138.618919
iter 10 value 94.055634
iter 20 value 91.012607
iter 30 value 85.114417
iter 40 value 85.107813
iter 50 value 83.466326
iter 60 value 83.437826
iter 70 value 83.415175
iter 80 value 83.378507
final value 83.378298
converged
Fitting Repeat 2
# weights: 305
initial value 97.334645
iter 10 value 94.076675
iter 20 value 94.070440
iter 20 value 94.070440
final value 94.070440
converged
Fitting Repeat 3
# weights: 305
initial value 99.208071
iter 10 value 93.678785
iter 20 value 93.672303
iter 30 value 93.670997
iter 40 value 93.670393
iter 50 value 93.668560
iter 60 value 93.665777
iter 70 value 93.482565
iter 80 value 83.481099
iter 90 value 82.977327
iter 100 value 82.205732
final value 82.205732
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 118.579591
iter 10 value 94.057477
iter 20 value 94.052952
iter 30 value 84.287534
iter 40 value 81.427263
iter 50 value 81.408578
iter 60 value 81.406753
iter 70 value 81.375828
iter 80 value 81.223154
iter 90 value 81.199813
iter 100 value 81.176954
final value 81.176954
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 97.635977
iter 10 value 85.479946
iter 20 value 84.859716
iter 30 value 84.838196
iter 40 value 84.835099
iter 50 value 84.763131
final value 84.758516
converged
Fitting Repeat 1
# weights: 507
initial value 107.953053
iter 10 value 93.878519
iter 20 value 93.873798
iter 30 value 93.868477
iter 40 value 93.863457
iter 50 value 93.859981
iter 60 value 93.533781
iter 70 value 92.371040
iter 80 value 86.246021
iter 90 value 85.536730
iter 100 value 85.389567
final value 85.389567
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.497798
iter 10 value 94.046474
iter 20 value 94.040056
iter 30 value 92.725007
iter 40 value 92.365477
iter 50 value 91.962576
iter 60 value 91.701200
iter 70 value 83.387652
iter 80 value 81.049681
iter 90 value 80.721705
iter 100 value 80.623666
final value 80.623666
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 96.001664
iter 10 value 94.045068
iter 20 value 94.038478
iter 30 value 94.038347
final value 94.038337
converged
Fitting Repeat 4
# weights: 507
initial value 130.020889
iter 10 value 94.061503
iter 20 value 94.040550
iter 30 value 93.147942
iter 40 value 88.947848
iter 50 value 86.317779
iter 60 value 84.340103
iter 70 value 84.315247
iter 80 value 84.126523
iter 90 value 83.179140
iter 100 value 82.655645
final value 82.655645
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 100.011974
iter 10 value 94.046692
iter 20 value 91.841218
iter 30 value 91.830813
iter 40 value 91.383782
iter 50 value 91.380776
iter 60 value 91.379235
final value 91.378993
converged
Fitting Repeat 1
# weights: 103
initial value 96.936624
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 102.270390
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.064040
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 99.085437
final value 94.032967
converged
Fitting Repeat 5
# weights: 103
initial value 99.241290
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 99.067898
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 106.081996
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 95.861972
final value 94.032967
converged
Fitting Repeat 4
# weights: 305
initial value 95.017402
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 97.892847
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 96.493723
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 107.827726
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 108.122275
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 114.039335
iter 10 value 85.157157
iter 20 value 84.929832
final value 84.929825
converged
Fitting Repeat 5
# weights: 507
initial value 119.674200
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 100.825794
iter 10 value 94.011727
iter 20 value 91.800769
iter 30 value 91.604579
iter 40 value 91.531073
iter 50 value 91.437761
iter 60 value 91.195743
iter 70 value 91.177119
iter 80 value 91.055819
iter 90 value 86.258042
iter 100 value 85.442250
final value 85.442250
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 98.186433
iter 10 value 94.115130
iter 20 value 93.872723
iter 30 value 87.070821
iter 40 value 83.999219
iter 50 value 83.215656
iter 60 value 82.287083
iter 70 value 81.851188
iter 80 value 81.284032
iter 90 value 80.977979
iter 100 value 80.807640
final value 80.807640
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 98.894722
iter 10 value 94.056796
iter 20 value 93.239102
iter 30 value 88.904233
iter 40 value 85.071960
iter 50 value 84.500392
iter 60 value 84.459286
iter 70 value 82.158575
iter 80 value 81.168528
iter 90 value 81.021784
final value 81.017757
converged
Fitting Repeat 4
# weights: 103
initial value 96.084266
iter 10 value 94.053177
iter 20 value 88.846740
iter 30 value 84.152391
iter 40 value 83.662985
iter 50 value 83.295538
iter 60 value 81.752472
iter 70 value 81.112964
iter 80 value 81.017808
final value 81.017757
converged
Fitting Repeat 5
# weights: 103
initial value 108.457118
iter 10 value 93.994533
iter 20 value 93.520717
iter 30 value 88.027004
iter 40 value 84.697651
iter 50 value 84.416921
iter 60 value 82.306744
iter 70 value 80.970263
iter 80 value 80.882853
iter 90 value 80.805302
final value 80.805297
converged
Fitting Repeat 1
# weights: 305
initial value 105.690220
iter 10 value 94.074542
iter 20 value 87.542294
iter 30 value 83.495864
iter 40 value 80.527123
iter 50 value 79.824817
iter 60 value 79.663448
iter 70 value 79.549833
iter 80 value 79.343643
iter 90 value 79.177213
iter 100 value 79.055122
final value 79.055122
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.900516
iter 10 value 86.912895
iter 20 value 84.301693
iter 30 value 82.002495
iter 40 value 81.003169
iter 50 value 80.241980
iter 60 value 79.977256
iter 70 value 79.663257
iter 80 value 79.395033
iter 90 value 79.385027
iter 100 value 79.381109
final value 79.381109
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.907452
iter 10 value 94.234659
iter 20 value 85.739910
iter 30 value 83.324118
iter 40 value 83.243667
iter 50 value 83.151416
iter 60 value 81.959301
iter 70 value 80.788324
iter 80 value 80.393714
iter 90 value 80.261629
iter 100 value 80.153586
final value 80.153586
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.946720
iter 10 value 94.136885
iter 20 value 89.116856
iter 30 value 83.115847
iter 40 value 82.352282
iter 50 value 82.211190
iter 60 value 81.410598
iter 70 value 80.559076
iter 80 value 79.974816
iter 90 value 79.636553
iter 100 value 79.614112
final value 79.614112
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.884163
iter 10 value 94.078179
iter 20 value 93.804625
iter 30 value 86.914389
iter 40 value 84.502830
iter 50 value 83.513234
iter 60 value 81.985178
iter 70 value 81.467293
iter 80 value 81.011050
iter 90 value 80.502457
iter 100 value 80.272752
final value 80.272752
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 113.517698
iter 10 value 94.700946
iter 20 value 93.299452
iter 30 value 90.383811
iter 40 value 84.380424
iter 50 value 82.912577
iter 60 value 80.441326
iter 70 value 80.214150
iter 80 value 79.853643
iter 90 value 79.533841
iter 100 value 79.362475
final value 79.362475
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 114.411816
iter 10 value 88.082778
iter 20 value 83.301475
iter 30 value 81.768893
iter 40 value 80.827610
iter 50 value 80.166385
iter 60 value 79.738264
iter 70 value 79.451476
iter 80 value 79.270057
iter 90 value 79.102367
iter 100 value 79.095249
final value 79.095249
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.276188
iter 10 value 94.498759
iter 20 value 94.065797
iter 30 value 93.378709
iter 40 value 87.654608
iter 50 value 83.842356
iter 60 value 82.980457
iter 70 value 82.248761
iter 80 value 82.050920
iter 90 value 81.785882
iter 100 value 81.291832
final value 81.291832
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 116.562129
iter 10 value 95.076057
iter 20 value 92.070064
iter 30 value 91.712187
iter 40 value 90.083997
iter 50 value 84.633551
iter 60 value 83.266014
iter 70 value 81.935312
iter 80 value 80.375724
iter 90 value 79.823732
iter 100 value 79.660744
final value 79.660744
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.385952
iter 10 value 93.214441
iter 20 value 92.172826
iter 30 value 91.544622
iter 40 value 82.937566
iter 50 value 82.139770
iter 60 value 81.305598
iter 70 value 80.266052
iter 80 value 79.860358
iter 90 value 79.698041
iter 100 value 79.501970
final value 79.501970
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.884244
iter 10 value 94.034350
iter 20 value 93.628123
iter 30 value 85.880655
iter 40 value 85.845918
iter 40 value 85.845917
iter 40 value 85.845917
final value 85.845917
converged
Fitting Repeat 2
# weights: 103
initial value 95.003577
final value 94.054538
converged
Fitting Repeat 3
# weights: 103
initial value 100.056272
iter 10 value 94.054588
iter 20 value 94.026119
iter 30 value 83.877804
iter 40 value 83.876238
iter 50 value 83.875614
iter 60 value 83.384999
iter 70 value 83.107306
iter 80 value 83.101216
iter 90 value 83.087565
iter 100 value 83.084026
final value 83.084026
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 95.582832
iter 10 value 94.054720
iter 20 value 94.052750
iter 30 value 93.904898
iter 40 value 93.878265
final value 93.878248
converged
Fitting Repeat 5
# weights: 103
initial value 99.529480
final value 94.054238
converged
Fitting Repeat 1
# weights: 305
initial value 99.000833
iter 10 value 94.058121
iter 20 value 91.629393
iter 30 value 87.164083
iter 40 value 86.866217
iter 50 value 84.774061
iter 60 value 80.125554
iter 70 value 79.652621
iter 80 value 78.856797
iter 90 value 78.817936
iter 100 value 78.570489
final value 78.570489
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.508942
iter 10 value 84.405365
iter 20 value 84.032568
iter 30 value 83.981895
iter 40 value 83.980853
iter 50 value 83.467525
iter 60 value 83.211706
iter 70 value 83.209889
final value 83.209622
converged
Fitting Repeat 3
# weights: 305
initial value 98.941480
iter 10 value 94.055868
iter 20 value 94.052949
final value 94.052924
converged
Fitting Repeat 4
# weights: 305
initial value 93.970326
iter 10 value 91.962504
iter 20 value 91.960964
final value 91.960778
converged
Fitting Repeat 5
# weights: 305
initial value 105.824351
iter 10 value 93.841374
iter 20 value 93.593688
iter 30 value 83.442085
iter 40 value 83.341977
final value 83.341944
converged
Fitting Repeat 1
# weights: 507
initial value 95.955195
iter 10 value 94.041842
iter 20 value 92.555955
iter 30 value 84.624504
iter 40 value 84.107460
final value 84.072940
converged
Fitting Repeat 2
# weights: 507
initial value 101.323876
iter 10 value 94.060718
iter 20 value 91.967606
iter 30 value 82.724774
iter 40 value 81.150483
iter 50 value 80.796172
iter 60 value 80.729828
iter 70 value 80.464564
iter 80 value 80.334687
iter 90 value 80.126624
iter 100 value 79.504954
final value 79.504954
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 96.362512
iter 10 value 94.041055
iter 20 value 94.032985
iter 30 value 92.807036
iter 40 value 88.313220
iter 50 value 88.209618
final value 88.209003
converged
Fitting Repeat 4
# weights: 507
initial value 99.446773
iter 10 value 93.821529
iter 20 value 93.816393
iter 30 value 93.811637
iter 40 value 92.563520
iter 50 value 83.732070
iter 60 value 81.936123
iter 70 value 80.373647
iter 80 value 79.602664
iter 90 value 79.440879
iter 100 value 78.930217
final value 78.930217
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 95.528686
iter 10 value 94.061342
iter 20 value 93.660590
iter 30 value 88.925267
iter 40 value 88.889637
iter 50 value 88.887971
iter 60 value 88.885658
iter 70 value 88.885332
iter 80 value 84.427208
iter 90 value 83.045135
iter 100 value 83.043374
final value 83.043374
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.156473
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 104.469822
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 100.825011
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 110.531808
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.290469
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 105.779431
iter 10 value 94.206006
iter 10 value 94.206006
iter 10 value 94.206006
final value 94.206006
converged
Fitting Repeat 2
# weights: 305
initial value 119.005815
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 101.423152
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 106.413377
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 99.202902
iter 10 value 93.695166
final value 93.694203
converged
Fitting Repeat 1
# weights: 507
initial value 109.911395
iter 10 value 93.796896
iter 20 value 93.765200
final value 93.765134
converged
Fitting Repeat 2
# weights: 507
initial value 109.785583
iter 10 value 87.986369
final value 86.588856
converged
Fitting Repeat 3
# weights: 507
initial value 100.043897
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 101.441000
iter 10 value 94.128946
iter 20 value 93.969101
iter 20 value 93.969101
iter 20 value 93.969101
final value 93.969101
converged
Fitting Repeat 5
# weights: 507
initial value 119.722101
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 104.504562
iter 10 value 94.488459
iter 20 value 92.385152
iter 30 value 90.687396
iter 40 value 90.082227
iter 50 value 82.993602
iter 60 value 82.127558
iter 70 value 81.769956
iter 80 value 81.596367
iter 90 value 81.558805
iter 100 value 80.847065
final value 80.847065
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.427547
iter 10 value 92.758685
iter 20 value 86.361051
iter 30 value 85.373261
iter 40 value 84.601989
iter 50 value 84.518398
iter 60 value 83.925216
iter 70 value 83.894848
iter 80 value 83.890826
iter 80 value 83.890826
final value 83.890826
converged
Fitting Repeat 3
# weights: 103
initial value 107.018919
iter 10 value 92.235414
iter 20 value 91.526877
iter 30 value 91.507707
iter 40 value 91.155341
iter 50 value 90.880517
iter 60 value 90.880106
final value 90.880100
converged
Fitting Repeat 4
# weights: 103
initial value 98.819524
iter 10 value 94.486447
iter 20 value 93.982289
iter 30 value 93.847877
iter 40 value 90.224439
iter 50 value 88.547811
iter 60 value 87.877062
iter 70 value 87.430891
iter 80 value 84.833556
iter 90 value 84.440202
iter 100 value 83.890986
final value 83.890986
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 106.027458
iter 10 value 94.361462
iter 20 value 92.551555
iter 30 value 91.488265
iter 40 value 90.243498
iter 50 value 86.507890
iter 60 value 86.131143
iter 70 value 85.093275
iter 80 value 81.693834
iter 90 value 81.082186
iter 100 value 80.922044
final value 80.922044
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 123.682412
iter 10 value 94.587212
iter 20 value 88.518370
iter 30 value 88.180028
iter 40 value 86.630585
iter 50 value 81.907497
iter 60 value 80.520241
iter 70 value 80.029131
iter 80 value 79.803922
iter 90 value 79.593908
iter 100 value 79.553361
final value 79.553361
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.456525
iter 10 value 94.301403
iter 20 value 89.727859
iter 30 value 86.790038
iter 40 value 85.890219
iter 50 value 85.156346
iter 60 value 85.106325
iter 70 value 84.922763
iter 80 value 82.060731
iter 90 value 80.425561
iter 100 value 79.763685
final value 79.763685
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.667993
iter 10 value 94.477528
iter 20 value 93.945989
iter 30 value 87.326534
iter 40 value 82.843632
iter 50 value 82.254022
iter 60 value 82.003304
iter 70 value 81.793166
iter 80 value 81.287811
iter 90 value 80.809602
iter 100 value 80.736875
final value 80.736875
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 117.280059
iter 10 value 94.487008
iter 20 value 92.131287
iter 30 value 85.076922
iter 40 value 84.169733
iter 50 value 82.809564
iter 60 value 81.697736
iter 70 value 81.545847
iter 80 value 81.496347
iter 90 value 81.452055
iter 100 value 81.409663
final value 81.409663
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 128.154341
iter 10 value 94.800030
iter 20 value 92.480217
iter 30 value 89.608996
iter 40 value 86.481660
iter 50 value 83.529143
iter 60 value 82.572205
iter 70 value 82.238856
iter 80 value 82.118527
iter 90 value 81.538387
iter 100 value 81.202229
final value 81.202229
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 108.932324
iter 10 value 95.034234
iter 20 value 94.452625
iter 30 value 92.719914
iter 40 value 86.301895
iter 50 value 82.864297
iter 60 value 81.107382
iter 70 value 80.155690
iter 80 value 79.455409
iter 90 value 79.249836
iter 100 value 79.121040
final value 79.121040
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.915390
iter 10 value 94.897303
iter 20 value 94.515741
iter 30 value 85.181711
iter 40 value 82.596894
iter 50 value 81.896244
iter 60 value 81.337638
iter 70 value 80.984582
iter 80 value 80.916683
iter 90 value 80.752254
iter 100 value 80.580109
final value 80.580109
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 120.935005
iter 10 value 94.439439
iter 20 value 89.254609
iter 30 value 86.170731
iter 40 value 85.528766
iter 50 value 85.269082
iter 60 value 84.586711
iter 70 value 84.218975
iter 80 value 83.124468
iter 90 value 82.200893
iter 100 value 80.225816
final value 80.225816
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.572735
iter 10 value 88.118019
iter 20 value 85.361541
iter 30 value 84.360624
iter 40 value 83.128474
iter 50 value 81.241961
iter 60 value 80.835649
iter 70 value 80.424508
iter 80 value 79.879127
iter 90 value 79.827554
iter 100 value 79.699520
final value 79.699520
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.380634
iter 10 value 94.591051
iter 20 value 94.170047
iter 30 value 87.597364
iter 40 value 84.397730
iter 50 value 83.732706
iter 60 value 81.860978
iter 70 value 81.618485
iter 80 value 80.734248
iter 90 value 79.909164
iter 100 value 79.743244
final value 79.743244
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.647395
iter 10 value 94.106463
iter 20 value 94.105875
iter 30 value 94.104238
final value 94.104179
converged
Fitting Repeat 2
# weights: 103
initial value 99.301878
final value 94.485899
converged
Fitting Repeat 3
# weights: 103
initial value 97.069314
final value 94.485910
converged
Fitting Repeat 4
# weights: 103
initial value 96.957110
iter 10 value 94.090518
iter 10 value 94.090517
iter 10 value 94.090517
final value 94.090517
converged
Fitting Repeat 5
# weights: 103
initial value 102.957210
iter 10 value 94.486065
iter 20 value 94.484251
final value 94.484213
converged
Fitting Repeat 1
# weights: 305
initial value 99.142958
iter 10 value 94.059749
iter 20 value 93.636235
iter 30 value 82.553100
iter 40 value 82.259886
iter 50 value 81.907201
iter 60 value 81.734131
iter 70 value 81.733854
iter 80 value 81.730405
iter 90 value 81.592713
iter 100 value 81.407148
final value 81.407148
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 94.912755
iter 10 value 94.359392
iter 20 value 94.353875
iter 30 value 90.000093
iter 40 value 85.375291
iter 50 value 84.066185
iter 60 value 83.434334
iter 70 value 83.245485
iter 80 value 83.109302
iter 90 value 80.203548
iter 100 value 79.119130
final value 79.119130
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.339350
iter 10 value 94.489254
iter 20 value 88.556763
iter 30 value 86.873574
iter 40 value 86.772399
iter 50 value 83.498148
iter 60 value 83.198993
iter 70 value 83.101973
iter 80 value 83.100822
final value 83.100779
converged
Fitting Repeat 4
# weights: 305
initial value 111.147341
iter 10 value 94.383796
iter 20 value 94.359315
iter 30 value 94.355242
iter 40 value 94.333110
iter 50 value 87.396101
iter 60 value 87.163232
iter 70 value 86.227140
iter 80 value 81.851715
iter 90 value 81.850930
iter 100 value 81.549458
final value 81.549458
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.083091
iter 10 value 94.359723
iter 20 value 94.240226
iter 30 value 94.073112
iter 40 value 84.032996
iter 50 value 82.941758
iter 60 value 82.136698
final value 82.136597
converged
Fitting Repeat 1
# weights: 507
initial value 113.492082
iter 10 value 94.492310
iter 20 value 94.460681
iter 30 value 93.788629
final value 93.788626
converged
Fitting Repeat 2
# weights: 507
initial value 99.761377
iter 10 value 87.762191
iter 20 value 83.706535
iter 30 value 83.174653
iter 40 value 83.149177
iter 50 value 82.245086
iter 60 value 81.787227
iter 70 value 81.203850
iter 80 value 80.964875
iter 90 value 80.842067
iter 100 value 80.797639
final value 80.797639
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 112.000249
iter 10 value 94.113706
iter 20 value 94.105921
iter 30 value 93.599267
iter 40 value 87.156795
final value 87.156751
converged
Fitting Repeat 4
# weights: 507
initial value 100.060674
iter 10 value 94.492327
iter 20 value 93.412856
iter 30 value 90.775318
iter 40 value 90.764759
iter 50 value 90.764163
final value 90.764091
converged
Fitting Repeat 5
# weights: 507
initial value 100.999460
iter 10 value 94.485911
iter 20 value 93.836699
iter 30 value 93.795104
iter 40 value 93.785439
iter 50 value 93.725660
iter 60 value 90.722600
iter 70 value 87.973235
iter 80 value 86.791521
iter 90 value 83.261897
iter 100 value 81.496254
final value 81.496254
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 112.073744
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.325508
iter 10 value 94.112903
iter 10 value 94.112903
iter 10 value 94.112903
final value 94.112903
converged
Fitting Repeat 3
# weights: 103
initial value 97.248912
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 109.559477
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.747151
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 96.715411
iter 10 value 87.325694
iter 20 value 86.850441
final value 86.850407
converged
Fitting Repeat 2
# weights: 305
initial value 95.617244
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 100.512097
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 98.651233
final value 94.484137
converged
Fitting Repeat 5
# weights: 305
initial value 94.551168
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 103.353482
iter 10 value 94.113164
final value 94.112903
converged
Fitting Repeat 2
# weights: 507
initial value 128.159452
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 118.472198
iter 10 value 94.111832
final value 94.111827
converged
Fitting Repeat 4
# weights: 507
initial value 96.382774
iter 10 value 94.482455
iter 20 value 94.464621
final value 94.443243
converged
Fitting Repeat 5
# weights: 507
initial value 95.305325
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 96.777799
iter 10 value 94.393079
iter 20 value 89.393952
iter 30 value 87.440329
iter 40 value 85.440020
iter 50 value 85.057976
iter 60 value 85.017625
iter 70 value 84.827079
iter 80 value 84.815195
final value 84.815192
converged
Fitting Repeat 2
# weights: 103
initial value 96.759122
iter 10 value 94.485035
iter 20 value 88.401593
iter 30 value 87.939975
iter 40 value 87.745270
iter 50 value 85.893859
iter 60 value 85.581252
iter 70 value 84.601763
iter 80 value 84.482166
iter 90 value 84.439628
final value 84.439626
converged
Fitting Repeat 3
# weights: 103
initial value 108.306387
iter 10 value 94.326697
iter 20 value 88.152976
iter 30 value 85.930352
iter 40 value 84.871315
iter 50 value 84.361120
iter 60 value 84.114591
iter 70 value 82.543420
iter 80 value 82.175717
iter 90 value 82.092389
iter 100 value 82.090347
final value 82.090347
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 104.036108
iter 10 value 92.607299
iter 20 value 85.468841
iter 30 value 85.190475
iter 40 value 85.078475
iter 50 value 83.889168
iter 60 value 82.565071
iter 70 value 82.300482
final value 82.296074
converged
Fitting Repeat 5
# weights: 103
initial value 102.423675
iter 10 value 92.064594
iter 20 value 88.936406
iter 30 value 88.317398
iter 40 value 86.061745
iter 50 value 83.436149
iter 60 value 83.097027
iter 70 value 82.901870
iter 80 value 82.517022
iter 90 value 82.306195
final value 82.296074
converged
Fitting Repeat 1
# weights: 305
initial value 107.645711
iter 10 value 94.627408
iter 20 value 94.441864
iter 30 value 94.194459
iter 40 value 85.841784
iter 50 value 85.141540
iter 60 value 84.895203
iter 70 value 84.821915
iter 80 value 84.798666
iter 90 value 83.666134
iter 100 value 83.338672
final value 83.338672
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.475759
iter 10 value 94.616738
iter 20 value 94.501095
iter 30 value 94.323683
iter 40 value 94.272474
iter 50 value 94.152941
iter 60 value 90.736855
iter 70 value 86.341697
iter 80 value 84.712919
iter 90 value 83.167993
iter 100 value 82.481172
final value 82.481172
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.035300
iter 10 value 94.435714
iter 20 value 92.297613
iter 30 value 87.815112
iter 40 value 87.421692
iter 50 value 85.452511
iter 60 value 83.960788
iter 70 value 82.541095
iter 80 value 82.342417
iter 90 value 82.230456
iter 100 value 82.060097
final value 82.060097
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.678616
iter 10 value 94.312109
iter 20 value 90.103365
iter 30 value 85.754542
iter 40 value 84.784089
iter 50 value 84.384247
iter 60 value 82.367987
iter 70 value 81.531152
iter 80 value 81.372760
iter 90 value 81.198499
iter 100 value 81.086525
final value 81.086525
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 121.858988
iter 10 value 94.457456
iter 20 value 87.376177
iter 30 value 85.591185
iter 40 value 84.844717
iter 50 value 83.952796
iter 60 value 83.298048
iter 70 value 82.814976
iter 80 value 82.255300
iter 90 value 81.420249
iter 100 value 81.176873
final value 81.176873
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.423681
iter 10 value 94.386861
iter 20 value 90.129795
iter 30 value 86.898786
iter 40 value 85.221144
iter 50 value 82.936496
iter 60 value 81.334824
iter 70 value 80.860186
iter 80 value 80.712102
iter 90 value 80.665932
iter 100 value 80.559745
final value 80.559745
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.489186
iter 10 value 94.394333
iter 20 value 89.884293
iter 30 value 86.983126
iter 40 value 84.026201
iter 50 value 83.505881
iter 60 value 83.113148
iter 70 value 82.398828
iter 80 value 81.453751
iter 90 value 81.172583
iter 100 value 81.137290
final value 81.137290
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 124.059209
iter 10 value 95.866214
iter 20 value 89.866389
iter 30 value 88.380884
iter 40 value 86.216451
iter 50 value 83.771607
iter 60 value 81.570494
iter 70 value 81.117491
iter 80 value 80.989203
iter 90 value 80.840300
iter 100 value 80.603531
final value 80.603531
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 121.307092
iter 10 value 94.681486
iter 20 value 94.384510
iter 30 value 92.478942
iter 40 value 91.752474
iter 50 value 87.768461
iter 60 value 85.746284
iter 70 value 85.390965
iter 80 value 85.125978
iter 90 value 84.004926
iter 100 value 82.944108
final value 82.944108
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 147.601578
iter 10 value 97.078500
iter 20 value 96.615263
iter 30 value 92.496330
iter 40 value 87.285010
iter 50 value 83.592049
iter 60 value 83.053450
iter 70 value 82.561598
iter 80 value 82.351834
iter 90 value 82.143249
iter 100 value 82.100079
final value 82.100079
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.844319
final value 94.485989
converged
Fitting Repeat 2
# weights: 103
initial value 96.676075
final value 94.485703
converged
Fitting Repeat 3
# weights: 103
initial value 102.733366
final value 94.485939
converged
Fitting Repeat 4
# weights: 103
initial value 99.088603
final value 94.485780
converged
Fitting Repeat 5
# weights: 103
initial value 118.206235
final value 94.486029
converged
Fitting Repeat 1
# weights: 305
initial value 104.186598
iter 10 value 94.488799
iter 20 value 94.478590
iter 30 value 90.134249
iter 40 value 86.132015
iter 50 value 86.109186
iter 60 value 86.036470
iter 70 value 84.267723
iter 80 value 83.349292
iter 90 value 83.341403
iter 100 value 83.266843
final value 83.266843
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 95.182252
iter 10 value 94.096050
iter 20 value 94.094515
iter 30 value 91.565688
iter 40 value 90.093140
iter 50 value 90.089987
iter 60 value 89.905310
final value 89.862318
converged
Fitting Repeat 3
# weights: 305
initial value 112.500730
iter 10 value 94.488704
iter 20 value 94.472696
iter 30 value 87.240898
iter 40 value 87.173980
iter 50 value 87.172198
iter 60 value 87.163966
iter 70 value 87.076467
iter 80 value 87.069750
iter 90 value 83.910727
iter 100 value 83.428252
final value 83.428252
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 94.473346
iter 10 value 92.263626
iter 20 value 92.263289
iter 30 value 92.199276
iter 40 value 92.133444
iter 50 value 92.132291
final value 92.132276
converged
Fitting Repeat 5
# weights: 305
initial value 101.844710
iter 10 value 94.489255
iter 20 value 94.484577
iter 30 value 94.387607
final value 94.113548
converged
Fitting Repeat 1
# weights: 507
initial value 94.694264
iter 10 value 94.122002
iter 20 value 94.111687
iter 30 value 94.054336
iter 40 value 93.933263
iter 50 value 89.588414
iter 60 value 87.042793
iter 70 value 86.461604
iter 80 value 86.233572
iter 90 value 82.657978
iter 100 value 80.873739
final value 80.873739
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 121.654295
iter 10 value 94.491760
iter 20 value 93.859875
iter 30 value 92.468016
iter 40 value 92.442153
final value 92.441818
converged
Fitting Repeat 3
# weights: 507
initial value 97.325512
iter 10 value 94.492030
iter 20 value 94.474522
iter 30 value 94.171984
final value 94.113345
converged
Fitting Repeat 4
# weights: 507
initial value 96.872969
iter 10 value 94.486505
iter 20 value 94.072081
iter 30 value 93.579087
iter 40 value 93.569790
iter 50 value 92.026803
iter 60 value 89.802450
iter 70 value 89.629969
iter 80 value 89.628212
final value 89.627216
converged
Fitting Repeat 5
# weights: 507
initial value 99.097730
iter 10 value 94.279708
iter 20 value 94.074956
iter 30 value 94.072504
iter 40 value 94.065514
iter 50 value 94.064295
final value 94.064254
converged
Fitting Repeat 1
# weights: 507
initial value 126.473622
iter 10 value 117.736797
iter 20 value 117.733025
iter 30 value 117.732686
iter 40 value 117.728958
iter 50 value 117.105643
iter 60 value 114.846760
iter 70 value 114.700870
iter 80 value 114.653665
iter 90 value 114.550329
final value 114.547837
converged
Fitting Repeat 2
# weights: 507
initial value 137.869287
iter 10 value 117.766105
iter 20 value 117.764952
iter 30 value 117.752904
iter 40 value 116.990292
iter 50 value 116.977517
iter 60 value 116.351891
iter 70 value 105.500696
iter 80 value 104.591161
iter 90 value 103.518611
iter 100 value 102.699339
final value 102.699339
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 123.985165
iter 10 value 117.894133
iter 20 value 117.078738
iter 30 value 107.056463
iter 40 value 105.346773
iter 50 value 105.334777
iter 60 value 105.252597
iter 70 value 105.244932
iter 80 value 105.244187
iter 90 value 105.206117
iter 100 value 105.198960
final value 105.198960
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 125.376494
iter 10 value 117.766736
iter 20 value 117.764369
iter 30 value 117.762235
iter 40 value 117.731088
iter 50 value 117.729641
final value 117.728948
converged
Fitting Repeat 5
# weights: 507
initial value 120.340138
iter 10 value 116.263176
iter 20 value 109.574417
iter 30 value 109.571077
iter 40 value 108.489080
iter 50 value 107.819762
iter 60 value 104.323699
iter 70 value 103.852056
iter 80 value 102.472473
iter 90 value 102.175317
iter 100 value 102.046938
final value 102.046938
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Mon Mar 16 01:18:37 2026
***********************************************
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
39.466 1.124 90.652
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 32.782 | 0.572 | 33.356 | |
| FreqInteractors | 0.426 | 0.035 | 0.461 | |
| calculateAAC | 0.031 | 0.001 | 0.032 | |
| calculateAutocor | 0.274 | 0.012 | 0.287 | |
| calculateCTDC | 0.070 | 0.001 | 0.071 | |
| calculateCTDD | 0.454 | 0.001 | 0.454 | |
| calculateCTDT | 0.147 | 0.001 | 0.147 | |
| calculateCTriad | 0.408 | 0.013 | 0.421 | |
| calculateDC | 0.135 | 0.007 | 0.141 | |
| calculateF | 0.302 | 0.003 | 0.306 | |
| calculateKSAAP | 0.100 | 0.007 | 0.107 | |
| calculateQD_Sm | 1.836 | 0.026 | 1.862 | |
| calculateTC | 1.495 | 0.158 | 1.653 | |
| calculateTC_Sm | 0.278 | 0.005 | 0.282 | |
| corr_plot | 36.721 | 0.421 | 37.909 | |
| enrichfindP | 0.520 | 0.047 | 11.642 | |
| enrichfind_hp | 0.036 | 0.002 | 0.996 | |
| enrichplot | 0.468 | 0.003 | 0.472 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.448 | 0.011 | 3.337 | |
| getHPI | 0.001 | 0.001 | 0.002 | |
| get_negativePPI | 0.003 | 0.001 | 0.004 | |
| get_positivePPI | 0.000 | 0.001 | 0.000 | |
| impute_missing_data | 0.002 | 0.002 | 0.004 | |
| plotPPI | 0.097 | 0.002 | 0.099 | |
| pred_ensembel | 12.607 | 0.102 | 11.430 | |
| var_imp | 33.646 | 0.486 | 34.135 | |