Matineh Rahmatbakhsh
| Snapshot Date: 2026-04-26 13:40 -0400 (Sun, 26 Apr 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 Build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-04-27 11:32 -0400 (Mon, 27 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4980 |
| 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 1029/2417 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.17.2 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | 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: 2026-04-27 01:00:51 -0400 (Mon, 27 Apr 2026) |
| EndedAt: 2026-04-27 01:16:14 -0400 (Mon, 27 Apr 2026) |
| EllapsedTime: 923.4 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 version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-04-27 05:00:51 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
FSmethod 34.356 0.512 34.905
corr_plot 34.113 0.346 34.509
var_imp 33.452 0.458 33.918
pred_ensembel 12.958 0.120 11.742
enrichfindP 0.590 0.039 9.713
* 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 version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
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
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 95.863258
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.167505
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 101.592756
final value 94.008696
converged
Fitting Repeat 4
# weights: 103
initial value 97.303540
final value 94.008696
converged
Fitting Repeat 5
# weights: 103
initial value 97.114507
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 99.809003
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 103.313155
iter 10 value 92.142308
iter 20 value 86.268755
final value 86.268064
converged
Fitting Repeat 3
# weights: 305
initial value 109.071280
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 110.719155
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 96.996242
iter 10 value 94.053018
final value 94.052911
converged
Fitting Repeat 1
# weights: 507
initial value 115.820073
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 96.701202
iter 10 value 93.640075
final value 93.609302
converged
Fitting Repeat 3
# weights: 507
initial value 119.507852
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 110.862768
iter 10 value 93.876543
iter 10 value 93.876543
iter 10 value 93.876543
final value 93.876543
converged
Fitting Repeat 5
# weights: 507
initial value 104.360502
iter 10 value 94.004167
iter 10 value 94.004167
iter 10 value 94.004167
final value 94.004167
converged
Fitting Repeat 1
# weights: 103
initial value 118.015564
iter 10 value 94.008462
iter 20 value 88.886760
iter 30 value 87.186401
iter 40 value 86.327162
iter 50 value 85.856580
iter 60 value 85.467530
iter 70 value 85.299631
iter 80 value 85.156049
iter 90 value 83.545982
iter 100 value 82.653899
final value 82.653899
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.945833
iter 10 value 94.059869
iter 20 value 93.874360
iter 30 value 87.525086
iter 40 value 86.849517
iter 50 value 86.624319
iter 60 value 86.492913
iter 70 value 86.262304
iter 80 value 85.600603
iter 90 value 82.823796
iter 100 value 82.800818
final value 82.800818
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 102.281469
iter 10 value 94.056711
iter 20 value 93.931209
iter 30 value 89.427045
iter 40 value 87.790419
iter 50 value 85.547190
iter 60 value 83.829801
iter 70 value 82.943291
iter 80 value 82.668231
iter 90 value 82.574920
iter 100 value 82.391745
final value 82.391745
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 97.028007
iter 10 value 94.057422
iter 20 value 90.726028
iter 30 value 85.588739
iter 40 value 84.757666
iter 50 value 84.713602
iter 60 value 84.632398
iter 70 value 84.629431
final value 84.629406
converged
Fitting Repeat 5
# weights: 103
initial value 97.498038
iter 10 value 94.057072
iter 20 value 90.495740
iter 30 value 86.735170
iter 40 value 86.526749
iter 50 value 86.373774
iter 60 value 85.845458
iter 70 value 83.575371
iter 80 value 82.605816
iter 90 value 82.578072
final value 82.577483
converged
Fitting Repeat 1
# weights: 305
initial value 104.962972
iter 10 value 94.092606
iter 20 value 93.006630
iter 30 value 90.443451
iter 40 value 86.021624
iter 50 value 83.622611
iter 60 value 82.096640
iter 70 value 81.770039
iter 80 value 81.507866
iter 90 value 81.397149
iter 100 value 81.388754
final value 81.388754
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.266227
iter 10 value 94.055848
iter 20 value 93.707597
iter 30 value 86.931134
iter 40 value 85.486883
iter 50 value 85.307706
iter 60 value 84.654833
iter 70 value 84.021702
iter 80 value 83.947410
iter 90 value 83.329964
iter 100 value 82.117711
final value 82.117711
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.936133
iter 10 value 91.760919
iter 20 value 87.385062
iter 30 value 86.991093
iter 40 value 85.973139
iter 50 value 84.816812
iter 60 value 84.673464
iter 70 value 84.524063
iter 80 value 84.329488
iter 90 value 83.305367
iter 100 value 82.998875
final value 82.998875
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 113.058320
iter 10 value 94.092994
iter 20 value 87.241697
iter 30 value 86.837885
iter 40 value 85.796746
iter 50 value 83.937220
iter 60 value 83.294880
iter 70 value 83.214274
iter 80 value 83.029446
iter 90 value 82.951607
iter 100 value 82.685705
final value 82.685705
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.787752
iter 10 value 94.141922
iter 20 value 90.131714
iter 30 value 86.982313
iter 40 value 83.818828
iter 50 value 82.389059
iter 60 value 81.642169
iter 70 value 81.394129
iter 80 value 81.307263
iter 90 value 81.252278
iter 100 value 81.199227
final value 81.199227
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 118.757502
iter 10 value 87.683624
iter 20 value 83.447745
iter 30 value 83.269494
iter 40 value 81.950434
iter 50 value 81.268420
iter 60 value 81.019566
iter 70 value 80.994103
iter 80 value 80.962307
iter 90 value 80.938525
iter 100 value 80.919168
final value 80.919168
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.976801
iter 10 value 93.819457
iter 20 value 88.629310
iter 30 value 85.874712
iter 40 value 83.574707
iter 50 value 82.676491
iter 60 value 82.112758
iter 70 value 81.676419
iter 80 value 81.397474
iter 90 value 81.136202
iter 100 value 81.024115
final value 81.024115
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.272061
iter 10 value 94.028923
iter 20 value 87.020062
iter 30 value 86.873024
iter 40 value 86.642811
iter 50 value 85.674319
iter 60 value 82.187283
iter 70 value 81.854534
iter 80 value 81.572472
iter 90 value 81.540939
iter 100 value 81.515362
final value 81.515362
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.258274
iter 10 value 94.109971
iter 20 value 92.793578
iter 30 value 89.389438
iter 40 value 86.555983
iter 50 value 83.559962
iter 60 value 82.356585
iter 70 value 81.994540
iter 80 value 81.597961
iter 90 value 81.494957
iter 100 value 81.426357
final value 81.426357
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 124.970103
iter 10 value 94.290910
iter 20 value 93.622892
iter 30 value 90.897364
iter 40 value 85.840775
iter 50 value 83.178444
iter 60 value 82.760046
iter 70 value 81.725143
iter 80 value 81.328548
iter 90 value 81.146789
iter 100 value 80.896346
final value 80.896346
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.779564
iter 10 value 93.674864
iter 20 value 93.674587
iter 30 value 93.637325
iter 40 value 93.636206
final value 93.636158
converged
Fitting Repeat 2
# weights: 103
initial value 102.064063
final value 94.054733
converged
Fitting Repeat 3
# weights: 103
initial value 108.649868
final value 94.054341
converged
Fitting Repeat 4
# weights: 103
initial value 96.321747
final value 94.054401
converged
Fitting Repeat 5
# weights: 103
initial value 99.410881
iter 10 value 92.595006
iter 20 value 86.732613
iter 30 value 86.718436
final value 86.718373
converged
Fitting Repeat 1
# weights: 305
initial value 94.234984
iter 10 value 93.727537
iter 20 value 93.652126
iter 30 value 86.345548
iter 40 value 85.894916
iter 50 value 85.514684
iter 60 value 84.874241
iter 70 value 82.564577
iter 80 value 81.705155
iter 90 value 81.684564
iter 100 value 81.684207
final value 81.684207
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.275834
iter 10 value 94.057956
iter 20 value 94.022615
iter 30 value 93.706019
iter 40 value 93.650052
final value 93.650044
converged
Fitting Repeat 3
# weights: 305
initial value 100.473732
iter 10 value 89.043363
iter 20 value 88.885389
iter 30 value 88.789591
iter 40 value 88.128725
iter 50 value 88.106817
iter 60 value 88.106577
iter 70 value 87.604378
iter 80 value 87.069235
iter 90 value 86.614896
iter 100 value 86.510478
final value 86.510478
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 112.065824
iter 10 value 94.013809
iter 20 value 93.491984
iter 30 value 91.531396
iter 40 value 91.333505
final value 91.333501
converged
Fitting Repeat 5
# weights: 305
initial value 95.625216
iter 10 value 93.084523
iter 20 value 93.022198
iter 30 value 93.012509
iter 40 value 92.973605
iter 50 value 92.952606
iter 60 value 92.951414
iter 70 value 92.949753
iter 80 value 92.696927
iter 90 value 92.663504
iter 100 value 92.377259
final value 92.377259
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.356409
iter 10 value 94.060822
iter 20 value 94.052731
iter 30 value 91.325659
iter 40 value 84.493932
iter 50 value 84.271155
iter 60 value 84.269315
final value 84.268556
converged
Fitting Repeat 2
# weights: 507
initial value 97.675628
iter 10 value 93.621376
iter 20 value 93.617188
iter 30 value 87.873429
iter 40 value 83.668940
iter 50 value 81.967523
iter 60 value 81.690845
iter 70 value 81.565528
iter 80 value 81.565122
iter 90 value 81.476350
iter 100 value 81.284374
final value 81.284374
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.145890
iter 10 value 93.985565
iter 20 value 93.974162
iter 30 value 91.684794
iter 40 value 88.006577
iter 50 value 87.974242
iter 60 value 87.706630
iter 70 value 87.635668
iter 80 value 87.635211
iter 90 value 85.644042
final value 85.595311
converged
Fitting Repeat 4
# weights: 507
initial value 109.643024
iter 10 value 94.061910
iter 20 value 87.170651
iter 30 value 85.409903
iter 40 value 85.386029
iter 50 value 85.375580
iter 60 value 85.276042
iter 70 value 85.268501
iter 80 value 85.015767
iter 90 value 84.542594
iter 100 value 84.429245
final value 84.429245
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.356939
iter 10 value 94.061202
iter 20 value 94.052942
iter 30 value 93.951557
iter 40 value 92.995072
iter 50 value 84.838923
iter 60 value 82.310993
iter 70 value 82.305166
iter 80 value 82.268451
iter 90 value 81.981241
iter 100 value 81.212661
final value 81.212661
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.877147
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 107.584387
final value 94.466823
converged
Fitting Repeat 3
# weights: 103
initial value 97.438993
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 96.572631
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 98.368245
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 118.978223
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 108.891049
iter 10 value 92.993213
final value 92.992978
converged
Fitting Repeat 3
# weights: 305
initial value 105.011505
final value 94.114232
converged
Fitting Repeat 4
# weights: 305
initial value 102.931856
iter 10 value 93.635051
final value 93.634811
converged
Fitting Repeat 5
# weights: 305
initial value 99.537195
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 120.295210
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 102.700408
iter 10 value 93.102862
final value 93.102857
converged
Fitting Repeat 3
# weights: 507
initial value 95.599189
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 102.009830
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 97.066222
final value 94.466823
converged
Fitting Repeat 1
# weights: 103
initial value 105.718474
iter 10 value 93.965601
iter 20 value 85.665840
iter 30 value 81.322009
iter 40 value 80.876327
iter 50 value 79.797138
iter 60 value 79.796044
iter 60 value 79.796043
iter 60 value 79.796043
final value 79.796043
converged
Fitting Repeat 2
# weights: 103
initial value 99.589776
iter 10 value 94.519816
iter 20 value 94.488352
iter 30 value 94.313391
iter 40 value 92.817355
iter 50 value 87.504536
iter 60 value 81.041403
iter 70 value 80.098849
iter 80 value 79.685735
iter 90 value 79.683359
iter 100 value 79.683241
final value 79.683241
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 103.718131
iter 10 value 94.485854
iter 20 value 94.036212
iter 30 value 92.121128
iter 40 value 91.864342
iter 50 value 91.698462
iter 60 value 91.015717
iter 70 value 90.591769
iter 80 value 90.295263
iter 90 value 90.282774
iter 90 value 90.282773
iter 90 value 90.282773
final value 90.282773
converged
Fitting Repeat 4
# weights: 103
initial value 96.770161
iter 10 value 94.486467
iter 10 value 94.486466
iter 20 value 93.499273
iter 30 value 90.218133
iter 40 value 89.857749
iter 50 value 88.635758
iter 60 value 84.252195
iter 70 value 83.297044
iter 80 value 81.763251
iter 90 value 81.383888
iter 100 value 81.270005
final value 81.270005
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 96.251813
iter 10 value 94.483468
iter 20 value 84.458625
iter 30 value 83.601054
iter 40 value 82.968283
iter 50 value 80.960063
iter 60 value 80.759174
iter 70 value 80.636418
iter 80 value 79.716516
iter 90 value 79.381423
iter 100 value 79.262577
final value 79.262577
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 106.450676
iter 10 value 94.039207
iter 20 value 85.872505
iter 30 value 84.152271
iter 40 value 82.446011
iter 50 value 79.129532
iter 60 value 78.081417
iter 70 value 77.774892
iter 80 value 77.643203
iter 90 value 77.595672
iter 100 value 77.481751
final value 77.481751
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 114.318344
iter 10 value 94.388756
iter 20 value 85.842996
iter 30 value 85.458335
iter 40 value 82.825318
iter 50 value 81.994929
iter 60 value 81.600464
iter 70 value 79.660251
iter 80 value 79.487482
iter 90 value 78.778478
iter 100 value 78.031760
final value 78.031760
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 117.354704
iter 10 value 94.525571
iter 20 value 87.519173
iter 30 value 80.407111
iter 40 value 80.015380
iter 50 value 79.590442
iter 60 value 79.245306
iter 70 value 78.683992
iter 80 value 77.944363
iter 90 value 76.758028
iter 100 value 75.952257
final value 75.952257
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 139.050581
iter 10 value 98.945151
iter 20 value 89.802119
iter 30 value 81.020751
iter 40 value 80.888762
iter 50 value 80.483682
iter 60 value 78.805503
iter 70 value 77.811042
iter 80 value 77.711204
iter 90 value 77.582885
iter 100 value 77.012792
final value 77.012792
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.722079
iter 10 value 94.514820
iter 20 value 94.449706
iter 30 value 88.850613
iter 40 value 81.204330
iter 50 value 81.106804
iter 60 value 80.710006
iter 70 value 79.821964
iter 80 value 79.624104
iter 90 value 78.050419
iter 100 value 76.713819
final value 76.713819
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 115.575291
iter 10 value 95.632754
iter 20 value 94.651954
iter 30 value 87.542919
iter 40 value 85.416124
iter 50 value 84.587656
iter 60 value 84.181528
iter 70 value 78.767896
iter 80 value 78.426191
iter 90 value 77.830057
iter 100 value 77.399067
final value 77.399067
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.079209
iter 10 value 94.689726
iter 20 value 94.031026
iter 30 value 86.138436
iter 40 value 84.310819
iter 50 value 83.115837
iter 60 value 82.761590
iter 70 value 82.636643
iter 80 value 82.582296
iter 90 value 82.474480
iter 100 value 81.376699
final value 81.376699
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.328640
iter 10 value 94.542318
iter 20 value 86.888948
iter 30 value 80.783448
iter 40 value 80.301996
iter 50 value 79.691328
iter 60 value 79.014712
iter 70 value 77.808584
iter 80 value 76.343412
iter 90 value 75.205449
iter 100 value 74.987590
final value 74.987590
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.720397
iter 10 value 94.557632
iter 20 value 94.199880
iter 30 value 91.700128
iter 40 value 82.863546
iter 50 value 79.971265
iter 60 value 79.394696
iter 70 value 78.230695
iter 80 value 77.809427
iter 90 value 77.370415
iter 100 value 77.195957
final value 77.195957
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 119.293599
iter 10 value 89.589648
iter 20 value 84.948102
iter 30 value 81.098438
iter 40 value 79.861223
iter 50 value 77.784614
iter 60 value 77.272163
iter 70 value 76.288438
iter 80 value 75.955476
iter 90 value 75.772840
iter 100 value 75.683720
final value 75.683720
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.478585
iter 10 value 94.485980
iter 20 value 94.453590
iter 30 value 82.665216
iter 40 value 81.086170
iter 50 value 81.081864
iter 60 value 78.558298
iter 70 value 78.033983
iter 80 value 77.696131
iter 90 value 77.618024
iter 100 value 77.613687
final value 77.613687
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.546980
final value 94.485823
converged
Fitting Repeat 3
# weights: 103
initial value 95.561280
final value 94.490858
converged
Fitting Repeat 4
# weights: 103
initial value 107.060132
final value 94.485456
converged
Fitting Repeat 5
# weights: 103
initial value 96.208866
final value 94.485742
converged
Fitting Repeat 1
# weights: 305
initial value 97.002933
iter 10 value 94.486579
iter 20 value 94.135389
iter 30 value 80.824774
iter 40 value 80.614123
iter 50 value 80.577805
iter 60 value 80.398783
iter 70 value 80.178871
iter 80 value 80.155134
iter 90 value 78.911358
iter 100 value 78.319703
final value 78.319703
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 140.642708
iter 10 value 94.489125
iter 20 value 94.483604
iter 30 value 91.388974
iter 40 value 91.372333
final value 91.372196
converged
Fitting Repeat 3
# weights: 305
initial value 96.485164
iter 10 value 94.488983
iter 20 value 93.105117
iter 30 value 92.773574
iter 40 value 85.019026
iter 50 value 84.988601
iter 60 value 84.942165
iter 70 value 84.939740
iter 80 value 84.939043
final value 84.938619
converged
Fitting Repeat 4
# weights: 305
initial value 127.150976
iter 10 value 94.491031
iter 20 value 94.457902
iter 30 value 93.674227
final value 93.674201
converged
Fitting Repeat 5
# weights: 305
initial value 98.473933
iter 10 value 94.488821
iter 20 value 94.178293
iter 30 value 89.678932
iter 40 value 89.603520
iter 50 value 88.621556
iter 60 value 88.236359
iter 70 value 84.809442
iter 80 value 83.738176
iter 90 value 83.737823
iter 100 value 83.734856
final value 83.734856
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.294338
iter 10 value 94.490744
iter 20 value 94.468388
final value 94.114391
converged
Fitting Repeat 2
# weights: 507
initial value 111.379021
iter 10 value 94.491385
iter 20 value 94.472902
iter 30 value 88.084807
iter 40 value 79.463160
iter 50 value 77.213445
iter 60 value 76.455171
iter 70 value 76.019363
iter 80 value 74.787869
iter 90 value 74.218900
iter 100 value 74.126384
final value 74.126384
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.773627
iter 10 value 94.475731
iter 20 value 94.441845
iter 30 value 82.607852
iter 40 value 82.471405
iter 40 value 82.471405
iter 40 value 82.471405
final value 82.471405
converged
Fitting Repeat 4
# weights: 507
initial value 120.907733
iter 10 value 92.933689
iter 20 value 92.828918
iter 30 value 86.860141
iter 40 value 85.777838
iter 50 value 85.540417
iter 60 value 85.426926
iter 70 value 85.425428
final value 85.424719
converged
Fitting Repeat 5
# weights: 507
initial value 122.512032
iter 10 value 94.493694
iter 20 value 94.451848
iter 30 value 85.015153
iter 40 value 79.886896
iter 50 value 79.666178
iter 60 value 79.665997
final value 79.665028
converged
Fitting Repeat 1
# weights: 103
initial value 97.781535
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.572338
iter 10 value 93.922223
iter 10 value 93.922222
iter 10 value 93.922222
final value 93.922222
converged
Fitting Repeat 3
# weights: 103
initial value 100.129509
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 100.522499
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 101.362242
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 118.559432
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 113.426051
iter 10 value 93.599194
iter 20 value 93.249415
final value 93.249411
converged
Fitting Repeat 3
# weights: 305
initial value 97.229348
iter 10 value 93.567525
iter 10 value 93.567525
iter 10 value 93.567525
final value 93.567525
converged
Fitting Repeat 4
# weights: 305
initial value 94.250974
final value 93.922222
converged
Fitting Repeat 5
# weights: 305
initial value 110.436118
final value 94.026542
converged
Fitting Repeat 1
# weights: 507
initial value 95.675306
iter 10 value 92.176390
iter 20 value 88.981978
iter 30 value 88.925701
iter 40 value 88.925475
final value 88.925474
converged
Fitting Repeat 2
# weights: 507
initial value 101.031956
final value 94.026542
converged
Fitting Repeat 3
# weights: 507
initial value 103.315444
iter 10 value 93.226988
iter 20 value 88.330455
iter 30 value 88.321998
final value 88.321995
converged
Fitting Repeat 4
# weights: 507
initial value 108.932647
final value 93.922222
converged
Fitting Repeat 5
# weights: 507
initial value 111.639278
final value 94.443241
converged
Fitting Repeat 1
# weights: 103
initial value 102.752750
iter 10 value 94.488874
iter 20 value 94.252231
iter 30 value 94.126061
iter 40 value 94.026355
iter 50 value 93.874610
iter 60 value 92.428824
iter 70 value 92.125212
iter 80 value 92.110538
iter 90 value 91.790464
iter 100 value 87.523516
final value 87.523516
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 114.664741
iter 10 value 94.480289
iter 20 value 92.084639
iter 30 value 86.945169
iter 40 value 85.570139
iter 50 value 85.048881
iter 60 value 85.012183
iter 60 value 85.012183
iter 60 value 85.012183
final value 85.012183
converged
Fitting Repeat 3
# weights: 103
initial value 101.991921
iter 10 value 94.199617
iter 20 value 93.635384
iter 30 value 93.578140
iter 40 value 92.509810
iter 50 value 90.249004
iter 60 value 89.201663
iter 70 value 88.619677
iter 80 value 88.572973
iter 90 value 87.463985
iter 100 value 84.068013
final value 84.068013
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.474024
iter 10 value 94.417956
iter 20 value 88.974000
iter 30 value 85.798587
iter 40 value 85.335543
iter 50 value 85.016843
iter 60 value 84.944871
iter 70 value 84.937366
final value 84.937365
converged
Fitting Repeat 5
# weights: 103
initial value 103.582002
iter 10 value 94.526505
iter 20 value 94.432401
iter 30 value 88.985086
iter 40 value 88.550423
iter 50 value 87.057821
iter 60 value 86.249416
iter 70 value 85.824591
iter 80 value 82.963325
iter 90 value 82.706322
iter 100 value 82.514965
final value 82.514965
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 107.362760
iter 10 value 94.225832
iter 20 value 93.069436
iter 30 value 92.420099
iter 40 value 85.561036
iter 50 value 84.174007
iter 60 value 83.617089
iter 70 value 83.188956
iter 80 value 82.005927
iter 90 value 81.526647
iter 100 value 81.373972
final value 81.373972
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.281869
iter 10 value 96.906028
iter 20 value 86.847926
iter 30 value 86.016452
iter 40 value 83.983133
iter 50 value 82.925549
iter 60 value 82.784216
iter 70 value 82.582048
iter 80 value 82.261731
iter 90 value 82.113904
iter 100 value 82.015908
final value 82.015908
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.394714
iter 10 value 93.530036
iter 20 value 91.701945
iter 30 value 87.753433
iter 40 value 84.122068
iter 50 value 82.152953
iter 60 value 81.845189
iter 70 value 81.803613
iter 80 value 81.681767
iter 90 value 81.551893
iter 100 value 81.295437
final value 81.295437
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.693104
iter 10 value 94.093925
iter 20 value 92.867705
iter 30 value 88.436929
iter 40 value 86.346947
iter 50 value 84.523403
iter 60 value 84.189251
iter 70 value 84.153484
iter 80 value 83.940974
iter 90 value 82.899905
iter 100 value 82.515659
final value 82.515659
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.008394
iter 10 value 94.468891
iter 20 value 92.778414
iter 30 value 89.735083
iter 40 value 87.524114
iter 50 value 85.965553
iter 60 value 82.863548
iter 70 value 82.514274
iter 80 value 82.171266
iter 90 value 82.006045
iter 100 value 81.448283
final value 81.448283
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 131.475163
iter 10 value 95.183821
iter 20 value 91.885470
iter 30 value 86.224672
iter 40 value 85.218145
iter 50 value 84.941678
iter 60 value 84.611157
iter 70 value 84.365173
iter 80 value 83.599486
iter 90 value 82.001111
iter 100 value 81.718120
final value 81.718120
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.485287
iter 10 value 94.235398
iter 20 value 93.142235
iter 30 value 90.940222
iter 40 value 85.952619
iter 50 value 83.473239
iter 60 value 82.747457
iter 70 value 81.924950
iter 80 value 81.671364
iter 90 value 81.170244
iter 100 value 80.855096
final value 80.855096
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 131.184800
iter 10 value 94.700316
iter 20 value 94.098914
iter 30 value 93.412704
iter 40 value 87.894617
iter 50 value 86.451207
iter 60 value 84.267435
iter 70 value 83.768371
iter 80 value 82.339866
iter 90 value 81.837006
iter 100 value 81.430814
final value 81.430814
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.812307
iter 10 value 94.472949
iter 20 value 93.126144
iter 30 value 85.764735
iter 40 value 85.124901
iter 50 value 83.581787
iter 60 value 82.938924
iter 70 value 82.189285
iter 80 value 82.029566
iter 90 value 81.985668
iter 100 value 81.797513
final value 81.797513
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 140.933371
iter 10 value 94.596132
iter 20 value 90.127637
iter 30 value 85.697795
iter 40 value 84.834964
iter 50 value 84.271423
iter 60 value 83.619046
iter 70 value 82.684974
iter 80 value 82.164717
iter 90 value 82.101954
iter 100 value 82.084741
final value 82.084741
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 117.750256
final value 94.485927
converged
Fitting Repeat 2
# weights: 103
initial value 98.814621
final value 94.485785
converged
Fitting Repeat 3
# weights: 103
initial value 107.612822
final value 94.485701
converged
Fitting Repeat 4
# weights: 103
initial value 96.845820
iter 10 value 94.008396
iter 20 value 93.977992
iter 30 value 93.976993
iter 40 value 93.934641
final value 93.923587
converged
Fitting Repeat 5
# weights: 103
initial value 100.745405
iter 10 value 94.028506
iter 20 value 94.027383
iter 30 value 85.479243
iter 40 value 84.292820
iter 50 value 84.219281
final value 84.219108
converged
Fitting Repeat 1
# weights: 305
initial value 102.960299
iter 10 value 94.488831
iter 20 value 93.361897
iter 30 value 87.613008
iter 40 value 87.239435
iter 50 value 87.234650
iter 60 value 87.231145
iter 70 value 86.576377
iter 80 value 86.575341
iter 90 value 85.997337
iter 100 value 85.292091
final value 85.292091
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.811612
iter 10 value 93.420565
iter 20 value 93.355398
iter 30 value 92.693083
iter 40 value 86.609548
iter 50 value 86.530156
iter 60 value 86.066043
iter 70 value 82.703190
iter 80 value 81.498946
iter 90 value 81.436627
iter 100 value 81.211752
final value 81.211752
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.314074
iter 10 value 93.385563
iter 20 value 93.356394
iter 30 value 92.689324
iter 40 value 87.741984
iter 50 value 86.616142
final value 86.607226
converged
Fitting Repeat 4
# weights: 305
initial value 110.405010
iter 10 value 94.489260
iter 20 value 94.341284
iter 30 value 94.038862
iter 40 value 93.422468
iter 50 value 93.353210
iter 60 value 93.352306
final value 93.352240
converged
Fitting Repeat 5
# weights: 305
initial value 118.629918
iter 10 value 94.031473
iter 20 value 94.026834
iter 30 value 93.353914
final value 93.351903
converged
Fitting Repeat 1
# weights: 507
initial value 100.648026
iter 10 value 94.491552
iter 20 value 93.998453
iter 30 value 83.974715
iter 40 value 83.539550
iter 50 value 83.069432
iter 60 value 83.048203
final value 83.048158
converged
Fitting Repeat 2
# weights: 507
initial value 121.141252
iter 10 value 93.930686
iter 20 value 93.922360
iter 30 value 87.299607
iter 40 value 86.491865
iter 50 value 83.594381
iter 60 value 83.519315
final value 83.518634
converged
Fitting Repeat 3
# weights: 507
initial value 123.590108
iter 10 value 94.492706
iter 20 value 94.456663
iter 30 value 93.864377
iter 40 value 93.423867
iter 50 value 85.248175
iter 60 value 85.164264
iter 70 value 84.674625
iter 80 value 84.375169
iter 90 value 84.372784
iter 100 value 84.371609
final value 84.371609
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.367172
iter 10 value 92.612693
iter 20 value 90.185660
iter 30 value 90.123093
iter 40 value 90.122083
iter 40 value 90.122083
final value 90.122083
converged
Fitting Repeat 5
# weights: 507
initial value 116.756225
iter 10 value 94.492399
iter 20 value 94.474165
iter 30 value 93.834619
iter 40 value 84.172144
iter 50 value 83.583690
iter 60 value 83.504488
iter 70 value 83.493503
iter 80 value 83.493149
iter 90 value 83.492777
iter 100 value 83.320065
final value 83.320065
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.412781
iter 10 value 90.993141
iter 20 value 84.135575
iter 30 value 83.125219
final value 83.125193
converged
Fitting Repeat 2
# weights: 103
initial value 94.506241
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.330449
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 101.602175
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 93.452677
iter 10 value 92.293947
iter 20 value 92.290793
final value 92.290780
converged
Fitting Repeat 1
# weights: 305
initial value 119.337888
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 116.976196
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 111.718955
iter 10 value 94.282829
final value 94.274404
converged
Fitting Repeat 4
# weights: 305
initial value 106.369926
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 100.455421
final value 94.409357
converged
Fitting Repeat 1
# weights: 507
initial value 102.199499
final value 93.903448
converged
Fitting Repeat 2
# weights: 507
initial value 104.491333
iter 10 value 93.002594
iter 20 value 92.910841
iter 30 value 92.905921
final value 92.905808
converged
Fitting Repeat 3
# weights: 507
initial value 100.077875
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 94.753781
iter 10 value 85.629469
iter 20 value 80.840068
iter 30 value 80.828115
final value 80.828067
converged
Fitting Repeat 5
# weights: 507
initial value 113.624737
iter 10 value 89.917727
iter 20 value 85.832845
final value 85.832095
converged
Fitting Repeat 1
# weights: 103
initial value 99.180045
iter 10 value 94.488593
iter 20 value 93.006288
iter 30 value 92.273763
iter 40 value 91.026638
iter 50 value 90.591421
iter 60 value 84.629797
iter 70 value 84.439504
iter 80 value 84.337827
iter 90 value 83.727672
iter 100 value 83.472387
final value 83.472387
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 99.435692
iter 10 value 94.489509
iter 20 value 84.428952
iter 30 value 83.491605
iter 40 value 83.252369
iter 50 value 83.138825
iter 60 value 82.768765
iter 70 value 81.990416
iter 80 value 81.969099
final value 81.968579
converged
Fitting Repeat 3
# weights: 103
initial value 113.464309
iter 10 value 94.469905
iter 20 value 90.796413
iter 30 value 89.537942
iter 40 value 84.659922
iter 50 value 83.126913
iter 60 value 82.604013
iter 70 value 82.442342
iter 80 value 82.300481
iter 90 value 82.290138
final value 82.289856
converged
Fitting Repeat 4
# weights: 103
initial value 99.631865
iter 10 value 93.458892
iter 20 value 88.709798
iter 30 value 86.782379
iter 40 value 85.893549
iter 50 value 83.865845
iter 60 value 83.099204
iter 70 value 83.076102
iter 80 value 83.060505
final value 83.060504
converged
Fitting Repeat 5
# weights: 103
initial value 98.992953
iter 10 value 94.489657
iter 20 value 91.671192
iter 30 value 85.707091
iter 40 value 82.195578
iter 50 value 81.929356
iter 60 value 81.616520
iter 70 value 81.261009
iter 80 value 80.896513
iter 90 value 80.457636
final value 80.451344
converged
Fitting Repeat 1
# weights: 305
initial value 121.501602
iter 10 value 94.413391
iter 20 value 91.428793
iter 30 value 83.359357
iter 40 value 83.236407
iter 50 value 83.029955
iter 60 value 82.464899
iter 70 value 81.848086
iter 80 value 81.434508
iter 90 value 79.823280
iter 100 value 79.368628
final value 79.368628
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.035525
iter 10 value 94.531218
iter 20 value 93.396217
iter 30 value 86.950565
iter 40 value 86.393107
iter 50 value 83.417056
iter 60 value 81.504852
iter 70 value 80.970733
iter 80 value 80.622755
iter 90 value 80.080876
iter 100 value 79.422768
final value 79.422768
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.507358
iter 10 value 94.357271
iter 20 value 93.748059
iter 30 value 84.469576
iter 40 value 82.934390
iter 50 value 82.558123
iter 60 value 81.435669
iter 70 value 80.493769
iter 80 value 79.900183
iter 90 value 79.650964
iter 100 value 79.095131
final value 79.095131
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.492960
iter 10 value 94.513113
iter 20 value 92.094957
iter 30 value 84.782197
iter 40 value 83.445487
iter 50 value 83.120469
iter 60 value 82.722742
iter 70 value 80.682096
iter 80 value 80.203474
iter 90 value 79.693315
iter 100 value 79.437488
final value 79.437488
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 117.628674
iter 10 value 94.355218
iter 20 value 88.505763
iter 30 value 85.075381
iter 40 value 84.372401
iter 50 value 83.980147
iter 60 value 80.995130
iter 70 value 80.854091
iter 80 value 80.729444
iter 90 value 80.301629
iter 100 value 80.249487
final value 80.249487
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 108.685926
iter 10 value 94.418334
iter 20 value 89.631360
iter 30 value 83.209263
iter 40 value 82.476447
iter 50 value 82.299003
iter 60 value 81.789294
iter 70 value 80.117626
iter 80 value 79.798341
iter 90 value 79.715449
iter 100 value 79.473335
final value 79.473335
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.991849
iter 10 value 95.336182
iter 20 value 92.371700
iter 30 value 85.658591
iter 40 value 83.716727
iter 50 value 83.228982
iter 60 value 82.782048
iter 70 value 82.223106
iter 80 value 81.811709
iter 90 value 81.429408
iter 100 value 80.063667
final value 80.063667
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.953358
iter 10 value 96.003782
iter 20 value 87.386857
iter 30 value 84.394271
iter 40 value 82.469877
iter 50 value 82.098179
iter 60 value 81.841258
iter 70 value 80.991207
iter 80 value 80.614051
iter 90 value 80.284359
iter 100 value 80.176480
final value 80.176480
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.411341
iter 10 value 94.663688
iter 20 value 93.322674
iter 30 value 86.487855
iter 40 value 82.818340
iter 50 value 81.008282
iter 60 value 80.520618
iter 70 value 79.859897
iter 80 value 79.581524
iter 90 value 79.369546
iter 100 value 78.451899
final value 78.451899
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 118.727364
iter 10 value 94.442284
iter 20 value 88.428317
iter 30 value 82.626423
iter 40 value 81.581905
iter 50 value 80.568403
iter 60 value 79.691444
iter 70 value 78.696507
iter 80 value 78.232499
iter 90 value 78.152218
iter 100 value 78.138802
final value 78.138802
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.747863
iter 10 value 86.326468
iter 20 value 86.067567
iter 30 value 84.308714
iter 40 value 83.414022
iter 50 value 83.349480
final value 83.349381
converged
Fitting Repeat 2
# weights: 103
initial value 96.977704
final value 94.485968
converged
Fitting Repeat 3
# weights: 103
initial value 100.438640
final value 94.485844
converged
Fitting Repeat 4
# weights: 103
initial value 99.744022
final value 94.486164
converged
Fitting Repeat 5
# weights: 103
initial value 96.549804
final value 94.486523
converged
Fitting Repeat 1
# weights: 305
initial value 113.824943
iter 10 value 94.489323
iter 20 value 86.455259
iter 30 value 83.745338
final value 83.745307
converged
Fitting Repeat 2
# weights: 305
initial value 97.281494
iter 10 value 86.705390
iter 20 value 85.770449
iter 30 value 85.449542
final value 85.420927
converged
Fitting Repeat 3
# weights: 305
initial value 107.950100
iter 10 value 94.489251
iter 20 value 87.272743
iter 30 value 82.631006
iter 40 value 82.624622
final value 82.624514
converged
Fitting Repeat 4
# weights: 305
initial value 98.213620
iter 10 value 94.489071
iter 20 value 86.390278
iter 30 value 82.827742
iter 40 value 82.371363
iter 50 value 81.152119
iter 60 value 80.843270
final value 80.729528
converged
Fitting Repeat 5
# weights: 305
initial value 101.192342
iter 10 value 94.280417
iter 20 value 94.260257
iter 30 value 83.534123
iter 40 value 81.246423
iter 50 value 81.224027
iter 60 value 81.219528
final value 81.219262
converged
Fitting Repeat 1
# weights: 507
initial value 97.865695
iter 10 value 94.491867
iter 20 value 94.392975
iter 30 value 90.244082
iter 40 value 86.212832
iter 50 value 86.076858
iter 60 value 86.073304
iter 70 value 86.068038
iter 80 value 86.048812
iter 90 value 84.549055
iter 100 value 84.297039
final value 84.297039
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 101.093155
iter 10 value 94.493216
iter 20 value 94.484393
iter 30 value 94.451858
iter 40 value 91.129555
iter 50 value 86.708463
iter 60 value 86.602553
iter 70 value 86.091653
iter 80 value 86.029260
iter 90 value 85.498642
iter 100 value 83.251068
final value 83.251068
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 97.064809
iter 10 value 94.353815
iter 20 value 94.283464
iter 30 value 94.183029
iter 40 value 92.083503
iter 50 value 91.762451
iter 60 value 91.531281
iter 70 value 91.497729
iter 80 value 90.937789
iter 90 value 85.326569
iter 100 value 84.631834
final value 84.631834
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.085001
iter 10 value 94.493074
iter 20 value 94.031433
iter 30 value 92.617400
iter 40 value 92.615855
iter 50 value 91.590949
iter 60 value 91.528752
final value 91.528544
converged
Fitting Repeat 5
# weights: 507
initial value 104.821890
iter 10 value 93.680971
iter 20 value 93.532270
iter 30 value 88.965341
iter 40 value 82.717475
iter 50 value 81.863385
iter 60 value 81.563028
iter 70 value 79.422733
iter 80 value 78.508758
iter 90 value 78.091270
iter 100 value 77.695713
final value 77.695713
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 108.752923
final value 93.371808
converged
Fitting Repeat 2
# weights: 103
initial value 98.444881
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 114.795742
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 94.727041
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 96.156849
final value 94.032967
converged
Fitting Repeat 1
# weights: 305
initial value 100.679719
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 100.428658
final value 93.869755
converged
Fitting Repeat 3
# weights: 305
initial value 101.628147
final value 94.032967
converged
Fitting Repeat 4
# weights: 305
initial value 92.558083
iter 10 value 86.231161
iter 20 value 86.034279
final value 86.034014
converged
Fitting Repeat 5
# weights: 305
initial value 101.988432
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 97.092530
final value 94.032967
converged
Fitting Repeat 2
# weights: 507
initial value 112.582565
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 109.768878
iter 10 value 94.033071
iter 20 value 94.032969
iter 20 value 94.032968
iter 20 value 94.032968
final value 94.032968
converged
Fitting Repeat 4
# weights: 507
initial value 104.805872
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 109.015446
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 98.261424
iter 10 value 94.054870
iter 20 value 94.010938
iter 30 value 87.318887
iter 40 value 85.375639
iter 50 value 85.155903
iter 60 value 84.846525
iter 70 value 84.619684
final value 84.618977
converged
Fitting Repeat 2
# weights: 103
initial value 96.489677
iter 10 value 94.050685
iter 20 value 90.791698
iter 30 value 88.689901
iter 40 value 84.991982
iter 50 value 84.796643
iter 60 value 84.635704
iter 70 value 84.602037
iter 80 value 83.518616
iter 90 value 83.137891
iter 100 value 82.619392
final value 82.619392
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.393222
iter 10 value 94.073836
iter 20 value 94.033478
iter 30 value 90.061152
iter 40 value 88.888410
iter 50 value 85.817680
iter 60 value 85.119604
iter 70 value 84.654228
iter 80 value 84.639456
iter 90 value 84.620892
final value 84.618977
converged
Fitting Repeat 4
# weights: 103
initial value 113.772677
iter 10 value 93.934454
iter 20 value 91.017617
iter 30 value 90.344304
iter 40 value 85.332808
iter 50 value 84.303827
iter 60 value 83.412719
iter 70 value 82.826047
iter 80 value 82.560405
iter 90 value 82.398355
iter 100 value 82.390633
final value 82.390633
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 109.480802
iter 10 value 93.933522
iter 20 value 88.956792
iter 30 value 85.584030
iter 40 value 84.079562
iter 50 value 82.684024
iter 60 value 82.190677
iter 70 value 82.092540
iter 80 value 82.032879
final value 82.027678
converged
Fitting Repeat 1
# weights: 305
initial value 125.171081
iter 10 value 94.954364
iter 20 value 94.136716
iter 30 value 93.116552
iter 40 value 86.820290
iter 50 value 84.348077
iter 60 value 82.484197
iter 70 value 81.790442
iter 80 value 81.223017
iter 90 value 80.722194
iter 100 value 80.590716
final value 80.590716
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.613385
iter 10 value 94.383270
iter 20 value 92.146023
iter 30 value 85.349476
iter 40 value 84.933285
iter 50 value 84.650629
iter 60 value 83.560904
iter 70 value 82.753470
iter 80 value 82.536353
iter 90 value 82.495835
iter 100 value 82.450981
final value 82.450981
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.676778
iter 10 value 94.144226
iter 20 value 93.615039
iter 30 value 88.895601
iter 40 value 88.842331
iter 50 value 88.274699
iter 60 value 83.140550
iter 70 value 82.870187
iter 80 value 82.571452
iter 90 value 82.276777
iter 100 value 81.559216
final value 81.559216
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.669040
iter 10 value 94.553383
iter 20 value 94.029717
iter 30 value 92.228771
iter 40 value 89.193916
iter 50 value 86.900099
iter 60 value 85.404716
iter 70 value 83.499528
iter 80 value 83.085278
iter 90 value 82.458584
iter 100 value 82.218830
final value 82.218830
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 127.017788
iter 10 value 94.359868
iter 20 value 94.072166
iter 30 value 89.420761
iter 40 value 87.938832
iter 50 value 86.981839
iter 60 value 85.669933
iter 70 value 84.766442
iter 80 value 84.010406
iter 90 value 83.088041
iter 100 value 82.839747
final value 82.839747
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 136.168021
iter 10 value 94.412454
iter 20 value 89.705068
iter 30 value 85.319820
iter 40 value 83.924849
iter 50 value 82.284067
iter 60 value 81.279505
iter 70 value 81.218530
iter 80 value 81.157088
iter 90 value 80.965139
iter 100 value 80.919507
final value 80.919507
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.611469
iter 10 value 93.239552
iter 20 value 88.203364
iter 30 value 84.756264
iter 40 value 83.378836
iter 50 value 81.986337
iter 60 value 81.902627
iter 70 value 81.396348
iter 80 value 80.861635
iter 90 value 80.549513
iter 100 value 80.490071
final value 80.490071
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 147.014747
iter 10 value 100.292396
iter 20 value 87.854982
iter 30 value 86.605909
iter 40 value 86.511376
iter 50 value 85.313977
iter 60 value 82.525745
iter 70 value 81.918717
iter 80 value 81.794055
iter 90 value 81.397075
iter 100 value 81.279011
final value 81.279011
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.611940
iter 10 value 94.924630
iter 20 value 90.363549
iter 30 value 87.780111
iter 40 value 86.417831
iter 50 value 84.368434
iter 60 value 82.703719
iter 70 value 81.600039
iter 80 value 81.233222
iter 90 value 81.083550
iter 100 value 81.008068
final value 81.008068
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.375137
iter 10 value 92.441161
iter 20 value 88.398607
iter 30 value 87.997454
iter 40 value 87.473485
iter 50 value 86.365957
iter 60 value 84.841965
iter 70 value 83.787764
iter 80 value 83.285199
iter 90 value 82.517924
iter 100 value 82.279215
final value 82.279215
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.760800
iter 10 value 94.034611
iter 20 value 93.748344
iter 30 value 83.745721
iter 40 value 83.735245
iter 50 value 83.733146
iter 60 value 82.607179
final value 82.575098
converged
Fitting Repeat 2
# weights: 103
initial value 99.207376
final value 94.054281
converged
Fitting Repeat 3
# weights: 103
initial value 103.147800
iter 10 value 94.054486
final value 94.053168
converged
Fitting Repeat 4
# weights: 103
initial value 97.295943
final value 94.034804
converged
Fitting Repeat 5
# weights: 103
initial value 106.770726
final value 94.054614
converged
Fitting Repeat 1
# weights: 305
initial value 108.537704
iter 10 value 94.058416
iter 20 value 94.051857
iter 30 value 88.424640
iter 40 value 83.031288
iter 50 value 82.834498
iter 60 value 82.807125
iter 70 value 82.760075
iter 80 value 82.757569
iter 90 value 82.757393
iter 100 value 82.757050
final value 82.757050
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 97.331535
iter 10 value 94.037370
iter 20 value 94.033308
final value 94.033033
converged
Fitting Repeat 3
# weights: 305
initial value 97.619071
iter 10 value 94.037872
iter 20 value 94.033848
iter 30 value 93.806459
iter 40 value 93.805111
final value 93.805004
converged
Fitting Repeat 4
# weights: 305
initial value 97.933095
iter 10 value 93.847757
iter 20 value 93.844164
iter 30 value 90.129520
iter 40 value 85.886468
iter 50 value 84.287524
iter 60 value 83.829818
final value 83.825476
converged
Fitting Repeat 5
# weights: 305
initial value 99.657488
iter 10 value 94.058015
iter 20 value 94.053019
iter 30 value 89.804080
iter 40 value 86.628359
iter 50 value 81.114780
iter 60 value 79.540984
iter 70 value 79.246419
iter 80 value 79.201665
iter 90 value 79.159178
iter 100 value 79.143602
final value 79.143602
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 99.038405
iter 10 value 94.060470
iter 20 value 93.687348
iter 30 value 93.089144
iter 40 value 93.088294
iter 40 value 93.088293
final value 93.088266
converged
Fitting Repeat 2
# weights: 507
initial value 100.949006
iter 10 value 94.046834
iter 20 value 94.040367
final value 94.039728
converged
Fitting Repeat 3
# weights: 507
initial value 106.456088
iter 10 value 94.041201
iter 20 value 93.952827
iter 30 value 86.131395
iter 40 value 83.949525
iter 50 value 81.884220
iter 60 value 81.035501
iter 70 value 80.317394
iter 80 value 80.240039
iter 90 value 80.200178
iter 100 value 80.200115
final value 80.200115
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.691585
iter 10 value 93.877567
iter 20 value 93.273570
iter 30 value 89.487905
iter 40 value 88.077849
iter 50 value 88.043278
final value 88.041868
converged
Fitting Repeat 5
# weights: 507
initial value 97.503798
iter 10 value 93.369600
iter 20 value 93.340831
iter 30 value 89.655912
iter 40 value 88.233050
iter 50 value 88.205674
final value 88.205646
converged
Fitting Repeat 1
# weights: 103
initial value 123.119509
final value 117.892141
converged
Fitting Repeat 2
# weights: 103
initial value 122.721695
final value 117.891920
converged
Fitting Repeat 3
# weights: 103
initial value 121.178474
final value 117.891898
converged
Fitting Repeat 4
# weights: 103
initial value 122.986726
final value 117.760397
converged
Fitting Repeat 5
# weights: 103
initial value 120.137569
final value 117.891923
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Mon Apr 27 01:06:23 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
40.251 1.356 108.786
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 34.356 | 0.512 | 34.905 | |
| FreqInteractors | 0.442 | 0.029 | 0.471 | |
| calculateAAC | 0.031 | 0.002 | 0.032 | |
| calculateAutocor | 0.262 | 0.019 | 0.282 | |
| calculateCTDC | 0.118 | 0.001 | 0.119 | |
| calculateCTDD | 0.475 | 0.000 | 0.475 | |
| calculateCTDT | 0.130 | 0.002 | 0.132 | |
| calculateCTriad | 0.419 | 0.005 | 0.425 | |
| calculateDC | 0.081 | 0.009 | 0.090 | |
| calculateF | 0.305 | 0.001 | 0.306 | |
| calculateKSAAP | 0.092 | 0.008 | 0.100 | |
| calculateQD_Sm | 1.877 | 0.023 | 1.901 | |
| calculateTC | 1.449 | 0.164 | 1.613 | |
| calculateTC_Sm | 0.292 | 0.003 | 0.294 | |
| corr_plot | 34.113 | 0.346 | 34.509 | |
| enrichfindP | 0.590 | 0.039 | 9.713 | |
| enrichfind_hp | 0.081 | 0.005 | 1.030 | |
| enrichplot | 0.506 | 0.002 | 0.509 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.455 | 0.006 | 3.631 | |
| getHPI | 0.001 | 0.002 | 0.002 | |
| get_negativePPI | 0.003 | 0.000 | 0.004 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.003 | 0.001 | 0.004 | |
| plotPPI | 0.097 | 0.001 | 0.098 | |
| pred_ensembel | 12.958 | 0.120 | 11.742 | |
| var_imp | 33.452 | 0.458 | 33.918 | |