Matineh Rahmatbakhsh
| Snapshot Date: 2025-12-21 13:40 -0500 (Sun, 21 Dec 2025) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: e6c77ab |
| git_last_commit_date: 2025-11-23 15:13:33 -0500 (Sun, 23 Nov 2025) |
| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2025-12-22 11:34 -0500 (Mon, 22 Dec 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2025-10-20 r88955) -- "Unsuffered Consequences" | 4878 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2025-11-04 r88984) -- "Unsuffered Consequences" | 4593 |
| 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 996/2332 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.17.1 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | WARNINGS | | ||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | OK | OK | WARNINGS | OK | | ||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.17.1 |
| 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_1.17.1.tar.gz |
| StartedAt: 2025-12-22 00:07:09 -0500 (Mon, 22 Dec 2025) |
| EndedAt: 2025-12-22 00:22:17 -0500 (Mon, 22 Dec 2025) |
| EllapsedTime: 908.3 seconds |
| RetCode: 0 |
| Status: WARNINGS |
| CheckDir: HPiP.Rcheck |
| Warnings: 1 |
##############################################################################
##############################################################################
###
### 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_1.17.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-10-20 r88955)
* 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 24.04.3 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.1’
* 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 ... WARNING
Codoc mismatches from Rd file 'pred_ensembel.Rd':
pred_ensembel
Code: function(features, gold_standard, classifier = c("avNNet",
"svmRadial", "ranger"), resampling.method = "cv",
ncross = 2, repeats = 2, verboseIter = TRUE, plots =
FALSE, filename = "plots.pdf")
Docs: function(features, gold_standard, classifier = c("avNNet",
"svmRadial", "ranger"), resampling.method = "cv",
ncross = 2, repeats = 2, verboseIter = TRUE, plots =
TRUE, filename = "plots.pdf")
Mismatches in argument default values:
Name: 'plots' Code: FALSE Docs: TRUE
* 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 34.723 0.582 35.377
var_imp 33.627 0.344 34.012
FSmethod 32.708 0.623 33.389
pred_ensembel 12.988 0.119 11.717
enrichfindP 0.576 0.039 15.471
getFASTA 0.439 0.007 7.148
* 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: 1 WARNING, 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 ‘1.17.1’ ** 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) (2025-10-20 r88955) -- "Unsuffered Consequences"
Copyright (C) 2025 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 101.264292
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.926548
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 103.840596
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 94.344191
iter 10 value 93.773046
final value 93.772973
converged
Fitting Repeat 5
# weights: 103
initial value 103.949482
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 103.183859
final value 94.052434
converged
Fitting Repeat 2
# weights: 305
initial value 94.856983
final value 94.052434
converged
Fitting Repeat 3
# weights: 305
initial value 96.516174
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 101.870607
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 96.156656
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 105.727167
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 102.007161
iter 10 value 94.466823
iter 10 value 94.466823
iter 10 value 94.466823
final value 94.466823
converged
Fitting Repeat 3
# weights: 507
initial value 100.790515
final value 94.466823
converged
Fitting Repeat 4
# weights: 507
initial value 101.078428
final value 94.139368
converged
Fitting Repeat 5
# weights: 507
initial value 103.253273
iter 10 value 93.809649
iter 10 value 93.809649
iter 10 value 93.809649
final value 93.809649
converged
Fitting Repeat 1
# weights: 103
initial value 100.406796
iter 10 value 94.487600
iter 20 value 86.699428
iter 30 value 85.494298
iter 40 value 85.358434
iter 50 value 84.747911
iter 60 value 82.265115
iter 70 value 80.967058
iter 80 value 80.494123
iter 90 value 80.258193
iter 100 value 80.224974
final value 80.224974
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 100.205538
iter 10 value 94.058896
iter 20 value 88.154176
iter 30 value 86.511148
iter 40 value 85.880266
iter 50 value 85.770703
iter 60 value 83.005917
iter 70 value 82.598070
iter 80 value 82.180010
iter 90 value 80.965598
iter 100 value 80.140225
final value 80.140225
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 100.778218
iter 10 value 93.726806
iter 20 value 93.397792
iter 30 value 90.681487
iter 40 value 90.384272
iter 50 value 88.659076
iter 60 value 83.803528
iter 70 value 83.572948
iter 80 value 82.801828
iter 90 value 81.486247
iter 100 value 80.578812
final value 80.578812
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.585994
iter 10 value 94.345787
iter 20 value 87.771650
iter 30 value 83.818836
iter 40 value 83.508512
iter 50 value 81.304143
iter 60 value 80.774470
iter 70 value 80.607793
iter 80 value 80.514286
iter 90 value 80.162609
final value 80.160548
converged
Fitting Repeat 5
# weights: 103
initial value 98.202006
iter 10 value 94.468866
iter 20 value 90.516618
iter 30 value 87.751055
iter 40 value 87.081943
iter 50 value 86.414374
iter 60 value 83.341904
iter 70 value 81.617611
iter 80 value 81.579035
iter 90 value 81.552731
iter 100 value 80.391680
final value 80.391680
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 99.857395
iter 10 value 91.489863
iter 20 value 85.348412
iter 30 value 82.843688
iter 40 value 80.500026
iter 50 value 79.565396
iter 60 value 79.433393
iter 70 value 79.349256
iter 80 value 79.112588
iter 90 value 78.694416
iter 100 value 78.486559
final value 78.486559
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.037106
iter 10 value 89.728691
iter 20 value 85.882285
iter 30 value 83.963002
iter 40 value 81.003691
iter 50 value 80.128109
iter 60 value 79.765580
iter 70 value 79.351400
iter 80 value 79.020833
iter 90 value 78.855700
iter 100 value 78.824930
final value 78.824930
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.270162
iter 10 value 94.233595
iter 20 value 87.767718
iter 30 value 86.152897
iter 40 value 84.405410
iter 50 value 80.730868
iter 60 value 80.072573
iter 70 value 79.715502
iter 80 value 79.184040
iter 90 value 78.897261
iter 100 value 78.622018
final value 78.622018
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 106.092297
iter 10 value 94.372789
iter 20 value 91.686921
iter 30 value 85.138714
iter 40 value 84.738090
iter 50 value 84.333820
iter 60 value 81.340159
iter 70 value 80.687147
iter 80 value 80.362879
iter 90 value 80.297253
iter 100 value 79.993669
final value 79.993669
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.293412
iter 10 value 94.508294
iter 20 value 89.091621
iter 30 value 85.373385
iter 40 value 83.091923
iter 50 value 80.551204
iter 60 value 80.107060
iter 70 value 79.863807
iter 80 value 79.331456
iter 90 value 78.567843
iter 100 value 78.443196
final value 78.443196
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.380299
iter 10 value 94.477021
iter 20 value 93.401006
iter 30 value 92.581393
iter 40 value 83.455313
iter 50 value 82.912981
iter 60 value 82.453929
iter 70 value 82.313080
iter 80 value 82.203382
iter 90 value 82.115667
iter 100 value 81.966597
final value 81.966597
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.219360
iter 10 value 94.662544
iter 20 value 94.426747
iter 30 value 93.785866
iter 40 value 86.135275
iter 50 value 84.597592
iter 60 value 83.619526
iter 70 value 83.001879
iter 80 value 82.082851
iter 90 value 81.269762
iter 100 value 80.196414
final value 80.196414
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 124.230379
iter 10 value 94.432698
iter 20 value 89.679426
iter 30 value 83.628264
iter 40 value 82.177776
iter 50 value 81.495320
iter 60 value 81.288786
iter 70 value 81.070455
iter 80 value 81.021154
iter 90 value 80.255603
iter 100 value 79.388328
final value 79.388328
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.576473
iter 10 value 94.211885
iter 20 value 91.141108
iter 30 value 87.601617
iter 40 value 86.365776
iter 50 value 83.295230
iter 60 value 82.348786
iter 70 value 82.001360
iter 80 value 81.038997
iter 90 value 80.126719
iter 100 value 79.917176
final value 79.917176
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.787308
iter 10 value 94.659172
iter 20 value 92.612365
iter 30 value 85.918787
iter 40 value 84.534851
iter 50 value 84.288763
iter 60 value 82.747812
iter 70 value 81.268413
iter 80 value 79.339673
iter 90 value 79.204572
iter 100 value 78.947517
final value 78.947517
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.430151
final value 94.485772
converged
Fitting Repeat 2
# weights: 103
initial value 100.869641
final value 94.485942
converged
Fitting Repeat 3
# weights: 103
initial value 96.589782
iter 10 value 93.811436
iter 20 value 93.808525
iter 30 value 93.793682
iter 40 value 93.793021
iter 40 value 93.793021
iter 40 value 93.793021
final value 93.793021
converged
Fitting Repeat 4
# weights: 103
initial value 106.726153
iter 10 value 94.466172
iter 20 value 94.054265
iter 30 value 93.379358
iter 40 value 93.231768
iter 50 value 93.231409
iter 60 value 93.230665
iter 70 value 93.230305
iter 70 value 93.230305
final value 93.230305
converged
Fitting Repeat 5
# weights: 103
initial value 99.327482
iter 10 value 94.484863
final value 94.484216
converged
Fitting Repeat 1
# weights: 305
initial value 96.154384
iter 10 value 94.057331
iter 20 value 94.052878
iter 30 value 93.297745
iter 40 value 93.273567
iter 50 value 93.273458
final value 93.273423
converged
Fitting Repeat 2
# weights: 305
initial value 99.319889
iter 10 value 94.489407
iter 20 value 94.488151
iter 30 value 94.479745
iter 40 value 93.649663
iter 50 value 90.079244
iter 60 value 85.660263
iter 70 value 84.840929
iter 80 value 84.764570
final value 84.762971
converged
Fitting Repeat 3
# weights: 305
initial value 111.431023
iter 10 value 93.778019
iter 20 value 93.775756
iter 30 value 93.751768
iter 40 value 93.748300
final value 93.748298
converged
Fitting Repeat 4
# weights: 305
initial value 108.044347
iter 10 value 94.485094
iter 20 value 94.410067
iter 30 value 87.048645
iter 40 value 84.460710
iter 50 value 81.744273
iter 60 value 81.695982
iter 70 value 81.515624
final value 81.515291
converged
Fitting Repeat 5
# weights: 305
initial value 100.251013
iter 10 value 94.488777
iter 20 value 94.306071
iter 30 value 93.307023
iter 40 value 93.304506
final value 93.304488
converged
Fitting Repeat 1
# weights: 507
initial value 107.557756
iter 10 value 89.061298
iter 20 value 85.504686
iter 30 value 85.497573
iter 40 value 85.222594
iter 50 value 84.609554
iter 60 value 84.608375
iter 70 value 84.468661
iter 80 value 82.457740
iter 90 value 81.000465
iter 100 value 79.416299
final value 79.416299
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.394485
iter 10 value 88.344122
iter 20 value 82.023949
iter 30 value 81.874488
iter 40 value 81.847842
iter 50 value 81.780046
iter 60 value 81.778463
iter 70 value 81.777102
final value 81.776156
converged
Fitting Repeat 3
# weights: 507
initial value 122.106675
iter 10 value 94.492345
iter 20 value 94.484915
iter 30 value 92.257659
iter 40 value 92.108025
iter 50 value 81.328581
iter 60 value 81.066641
iter 70 value 81.058253
iter 80 value 81.009620
iter 90 value 81.008305
iter 100 value 81.007376
final value 81.007376
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 102.334768
iter 10 value 93.710705
iter 20 value 88.655771
iter 30 value 81.913203
iter 40 value 81.905422
iter 50 value 81.905251
iter 60 value 81.061597
iter 70 value 81.023098
final value 81.008411
converged
Fitting Repeat 5
# weights: 507
initial value 120.711416
iter 10 value 86.142742
iter 20 value 84.510971
iter 30 value 84.184231
iter 40 value 84.058546
iter 50 value 84.057401
iter 60 value 84.053839
iter 70 value 84.049917
iter 80 value 84.038677
iter 90 value 83.723725
iter 100 value 82.750907
final value 82.750907
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.912895
final value 94.484053
converged
Fitting Repeat 2
# weights: 103
initial value 100.000185
final value 93.772973
converged
Fitting Repeat 3
# weights: 103
initial value 97.551202
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.927188
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 102.605737
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 114.738254
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 105.535106
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 114.529757
iter 10 value 93.103484
iter 20 value 92.205982
iter 30 value 92.204560
final value 92.204558
converged
Fitting Repeat 4
# weights: 305
initial value 110.130659
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 102.811439
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 105.641699
final value 94.026542
converged
Fitting Repeat 2
# weights: 507
initial value 112.102877
iter 10 value 94.165118
iter 10 value 94.165117
iter 10 value 94.165117
final value 94.165117
converged
Fitting Repeat 3
# weights: 507
initial value 124.885906
final value 93.320225
converged
Fitting Repeat 4
# weights: 507
initial value 104.876017
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 95.626972
final value 94.026542
converged
Fitting Repeat 1
# weights: 103
initial value 96.289586
iter 10 value 94.399547
iter 20 value 94.080240
iter 30 value 93.442459
iter 40 value 93.140847
iter 50 value 92.715548
iter 60 value 88.430050
iter 70 value 83.336798
iter 80 value 80.927909
iter 90 value 80.892309
iter 100 value 80.887806
final value 80.887806
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.445209
iter 10 value 95.075239
iter 20 value 94.481380
iter 30 value 94.218923
iter 40 value 94.137942
iter 50 value 92.992085
iter 60 value 89.319725
iter 70 value 88.540852
iter 80 value 88.040541
iter 90 value 86.682702
iter 100 value 85.848275
final value 85.848275
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.285583
iter 10 value 93.894332
iter 20 value 91.865191
iter 30 value 91.257591
iter 40 value 85.637772
iter 50 value 84.533153
iter 60 value 83.976249
iter 70 value 82.963784
iter 80 value 82.080020
iter 90 value 81.355717
iter 100 value 80.987659
final value 80.987659
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.483607
iter 10 value 94.144088
iter 20 value 93.675839
iter 30 value 86.193005
iter 40 value 85.693729
iter 50 value 85.581326
iter 60 value 85.552859
final value 85.552844
converged
Fitting Repeat 5
# weights: 103
initial value 97.243918
iter 10 value 94.484343
iter 20 value 90.225505
iter 30 value 88.763577
iter 40 value 87.374516
iter 50 value 86.311972
iter 60 value 84.298250
iter 70 value 83.652502
iter 80 value 83.627621
final value 83.627615
converged
Fitting Repeat 1
# weights: 305
initial value 114.981440
iter 10 value 94.549912
iter 20 value 92.605563
iter 30 value 87.267696
iter 40 value 85.956079
iter 50 value 84.760396
iter 60 value 83.976160
iter 70 value 81.102563
iter 80 value 80.521070
iter 90 value 79.954041
iter 100 value 79.885846
final value 79.885846
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 126.767094
iter 10 value 95.821535
iter 20 value 94.784750
iter 30 value 91.913470
iter 40 value 91.157168
iter 50 value 91.043939
iter 60 value 90.542323
iter 70 value 90.245224
iter 80 value 89.539170
iter 90 value 88.822221
iter 100 value 85.065956
final value 85.065956
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.976683
iter 10 value 93.682840
iter 20 value 90.064954
iter 30 value 87.740128
iter 40 value 86.973700
iter 50 value 86.386524
iter 60 value 85.292553
iter 70 value 83.091488
iter 80 value 82.054819
iter 90 value 80.104616
iter 100 value 79.612462
final value 79.612462
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.072788
iter 10 value 93.719197
iter 20 value 93.575469
iter 30 value 89.979124
iter 40 value 86.517553
iter 50 value 84.961005
iter 60 value 83.171059
iter 70 value 81.250741
iter 80 value 81.018486
iter 90 value 80.849928
iter 100 value 80.465181
final value 80.465181
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.391786
iter 10 value 92.553706
iter 20 value 88.649294
iter 30 value 88.033517
iter 40 value 86.094614
iter 50 value 83.329535
iter 60 value 80.444181
iter 70 value 80.128967
iter 80 value 79.910741
iter 90 value 79.902415
iter 100 value 79.898351
final value 79.898351
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.319903
iter 10 value 94.515240
iter 20 value 93.280120
iter 30 value 87.750491
iter 40 value 84.302413
iter 50 value 81.753106
iter 60 value 80.968924
iter 70 value 80.635647
iter 80 value 80.037350
iter 90 value 79.972250
iter 100 value 79.960370
final value 79.960370
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 112.922989
iter 10 value 94.959820
iter 20 value 94.403290
iter 30 value 93.632033
iter 40 value 91.567163
iter 50 value 89.110677
iter 60 value 87.911822
iter 70 value 84.188819
iter 80 value 82.053950
iter 90 value 81.204216
iter 100 value 81.114129
final value 81.114129
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 134.952704
iter 10 value 94.670753
iter 20 value 93.500094
iter 30 value 92.919067
iter 40 value 86.483519
iter 50 value 83.287686
iter 60 value 80.968872
iter 70 value 80.424413
iter 80 value 80.072755
iter 90 value 79.518305
iter 100 value 79.236779
final value 79.236779
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 123.359264
iter 10 value 99.944910
iter 20 value 88.468193
iter 30 value 87.134206
iter 40 value 84.717854
iter 50 value 80.863460
iter 60 value 80.447276
iter 70 value 80.078957
iter 80 value 79.742664
iter 90 value 79.481564
iter 100 value 79.249813
final value 79.249813
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.789689
iter 10 value 97.945854
iter 20 value 90.023971
iter 30 value 85.344816
iter 40 value 83.527949
iter 50 value 83.154869
iter 60 value 81.823229
iter 70 value 80.717475
iter 80 value 80.371244
iter 90 value 80.051865
iter 100 value 79.780415
final value 79.780415
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.666619
final value 94.485743
converged
Fitting Repeat 2
# weights: 103
initial value 104.668781
final value 94.485997
converged
Fitting Repeat 3
# weights: 103
initial value 95.926056
final value 94.485924
converged
Fitting Repeat 4
# weights: 103
initial value 96.811044
final value 94.486007
converged
Fitting Repeat 5
# weights: 103
initial value 97.223048
final value 94.486103
converged
Fitting Repeat 1
# weights: 305
initial value 110.036397
iter 10 value 94.489081
iter 20 value 94.484431
final value 94.484222
converged
Fitting Repeat 2
# weights: 305
initial value 96.506597
iter 10 value 94.488987
iter 20 value 94.484327
iter 30 value 94.474185
iter 40 value 87.836332
iter 50 value 87.004772
iter 60 value 86.728928
iter 70 value 85.945999
iter 80 value 83.939663
iter 90 value 81.980993
iter 100 value 79.322428
final value 79.322428
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.196856
iter 10 value 90.493026
iter 20 value 88.547297
iter 30 value 87.290644
iter 40 value 87.269279
iter 50 value 83.716806
iter 60 value 83.514116
iter 70 value 81.487562
iter 80 value 80.955799
iter 90 value 80.102358
iter 100 value 80.100305
final value 80.100305
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 95.440043
iter 10 value 94.031539
iter 20 value 93.975751
final value 93.974868
converged
Fitting Repeat 5
# weights: 305
initial value 99.318923
iter 10 value 94.489601
iter 20 value 93.907682
iter 30 value 93.661080
final value 93.659993
converged
Fitting Repeat 1
# weights: 507
initial value 97.291490
iter 10 value 93.328731
iter 20 value 93.306626
iter 30 value 93.247707
iter 40 value 92.103219
iter 50 value 85.102820
iter 60 value 84.982994
iter 70 value 84.532313
iter 80 value 84.524885
iter 90 value 84.519977
iter 100 value 84.265148
final value 84.265148
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 99.203432
iter 10 value 93.648673
iter 20 value 93.626155
iter 30 value 93.257953
iter 40 value 93.192303
iter 50 value 90.834893
iter 60 value 90.829939
iter 70 value 90.829806
iter 80 value 90.828860
iter 90 value 90.447530
iter 100 value 83.982970
final value 83.982970
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 96.433909
iter 10 value 94.492378
iter 20 value 94.484198
iter 30 value 93.322582
iter 40 value 93.321757
iter 50 value 93.321461
iter 60 value 93.321009
iter 60 value 93.321009
iter 60 value 93.321009
final value 93.321009
converged
Fitting Repeat 4
# weights: 507
initial value 105.668329
iter 10 value 93.851739
iter 20 value 93.849547
iter 30 value 93.597285
iter 40 value 93.594259
iter 50 value 93.572392
iter 60 value 93.549996
final value 93.549537
converged
Fitting Repeat 5
# weights: 507
initial value 103.744882
iter 10 value 93.429630
iter 20 value 93.327804
iter 30 value 92.990346
iter 40 value 87.314584
iter 50 value 85.133490
iter 60 value 84.454947
iter 70 value 84.380235
iter 80 value 84.378576
iter 90 value 83.716800
iter 100 value 83.149376
final value 83.149376
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.444835
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 101.766601
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 98.609340
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.958022
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 95.691052
iter 10 value 91.129518
iter 20 value 91.078598
final value 91.078446
converged
Fitting Repeat 1
# weights: 305
initial value 108.759939
iter 10 value 93.795743
final value 93.785768
converged
Fitting Repeat 2
# weights: 305
initial value 96.791754
iter 10 value 90.302927
iter 20 value 85.385844
iter 30 value 85.018574
iter 40 value 84.982605
iter 50 value 84.695315
final value 84.694864
converged
Fitting Repeat 3
# weights: 305
initial value 95.653029
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 97.298448
iter 10 value 89.544525
iter 20 value 85.473704
iter 30 value 85.390085
final value 85.387942
converged
Fitting Repeat 5
# weights: 305
initial value 101.058757
final value 93.836066
converged
Fitting Repeat 1
# weights: 507
initial value 96.361627
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 99.124992
iter 10 value 90.002023
iter 20 value 89.989660
iter 20 value 89.989659
iter 20 value 89.989659
final value 89.989659
converged
Fitting Repeat 3
# weights: 507
initial value 112.954850
iter 10 value 93.292481
iter 20 value 93.288895
final value 93.288890
converged
Fitting Repeat 4
# weights: 507
initial value 96.840042
final value 93.836066
converged
Fitting Repeat 5
# weights: 507
initial value 124.685244
final value 93.903448
converged
Fitting Repeat 1
# weights: 103
initial value 98.708703
iter 10 value 94.056230
iter 20 value 91.200197
iter 30 value 86.747812
iter 40 value 86.417601
iter 50 value 86.009416
iter 60 value 84.670665
iter 70 value 81.546330
iter 80 value 81.106539
iter 90 value 80.863821
iter 100 value 80.778782
final value 80.778782
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.029587
iter 10 value 94.058886
iter 20 value 94.054341
iter 30 value 93.975935
iter 40 value 93.865766
iter 50 value 93.856388
iter 60 value 93.852068
iter 70 value 93.845303
iter 80 value 89.932052
iter 90 value 83.930739
iter 100 value 83.733484
final value 83.733484
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 99.440733
iter 10 value 94.058732
iter 20 value 94.043861
iter 30 value 92.177358
iter 40 value 92.019555
iter 50 value 89.193952
iter 60 value 86.432040
iter 70 value 85.788823
iter 80 value 85.182602
iter 90 value 85.085751
iter 100 value 85.019633
final value 85.019633
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 102.235579
iter 10 value 94.055543
iter 20 value 83.848934
iter 30 value 83.741128
iter 40 value 83.511663
iter 50 value 82.795154
iter 60 value 82.054175
iter 70 value 81.878971
iter 80 value 81.827421
final value 81.825788
converged
Fitting Repeat 5
# weights: 103
initial value 96.734861
iter 10 value 92.076303
iter 20 value 83.978932
iter 30 value 83.702730
iter 40 value 82.687037
iter 50 value 82.161560
iter 60 value 82.096229
iter 70 value 82.070945
final value 82.070912
converged
Fitting Repeat 1
# weights: 305
initial value 102.003291
iter 10 value 94.277415
iter 20 value 90.528171
iter 30 value 83.454676
iter 40 value 82.662691
iter 50 value 82.319898
iter 60 value 81.107791
iter 70 value 80.590962
iter 80 value 80.503987
iter 90 value 80.090709
iter 100 value 79.712284
final value 79.712284
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.931337
iter 10 value 94.116467
iter 20 value 94.050161
iter 30 value 90.964406
iter 40 value 88.946659
iter 50 value 88.859227
iter 60 value 88.369660
iter 70 value 80.915728
iter 80 value 79.881582
iter 90 value 79.736940
iter 100 value 79.565042
final value 79.565042
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.305370
iter 10 value 94.026873
iter 20 value 93.832668
iter 30 value 89.950936
iter 40 value 84.038053
iter 50 value 83.843236
iter 60 value 83.520383
iter 70 value 82.145400
iter 80 value 81.813277
iter 90 value 81.619556
iter 100 value 81.521687
final value 81.521687
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.555848
iter 10 value 93.718369
iter 20 value 85.152579
iter 30 value 83.307783
iter 40 value 82.449691
iter 50 value 81.958375
iter 60 value 81.874636
iter 70 value 80.659357
iter 80 value 79.775188
iter 90 value 79.636287
iter 100 value 79.473475
final value 79.473475
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.911814
iter 10 value 92.770551
iter 20 value 86.788990
iter 30 value 83.731905
iter 40 value 81.476423
iter 50 value 80.469920
iter 60 value 80.180895
iter 70 value 79.988126
iter 80 value 79.827466
iter 90 value 79.656284
iter 100 value 79.624249
final value 79.624249
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 117.388203
iter 10 value 92.242868
iter 20 value 85.843155
iter 30 value 85.094891
iter 40 value 82.406787
iter 50 value 81.740974
iter 60 value 81.414057
iter 70 value 80.962159
iter 80 value 80.127158
iter 90 value 79.788939
iter 100 value 79.492948
final value 79.492948
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.858516
iter 10 value 95.861460
iter 20 value 94.068613
iter 30 value 94.017179
iter 40 value 85.433117
iter 50 value 83.965514
iter 60 value 82.736408
iter 70 value 81.844091
iter 80 value 81.346414
iter 90 value 81.052728
iter 100 value 80.928852
final value 80.928852
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 121.783087
iter 10 value 95.527906
iter 20 value 93.434782
iter 30 value 91.573052
iter 40 value 91.512810
iter 50 value 90.159677
iter 60 value 87.823158
iter 70 value 86.682772
iter 80 value 82.973102
iter 90 value 80.317009
iter 100 value 79.871466
final value 79.871466
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 124.015768
iter 10 value 93.402876
iter 20 value 85.935427
iter 30 value 83.791689
iter 40 value 82.086323
iter 50 value 80.692395
iter 60 value 80.197682
iter 70 value 79.654481
iter 80 value 79.419552
iter 90 value 79.337916
iter 100 value 79.313121
final value 79.313121
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.058953
iter 10 value 95.632496
iter 20 value 94.064040
iter 30 value 88.279793
iter 40 value 85.895984
iter 50 value 83.027139
iter 60 value 82.707196
iter 70 value 82.442955
iter 80 value 82.134313
iter 90 value 81.718253
iter 100 value 81.211454
final value 81.211454
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.827461
final value 94.054566
converged
Fitting Repeat 2
# weights: 103
initial value 94.168540
final value 94.054589
converged
Fitting Repeat 3
# weights: 103
initial value 104.537506
final value 94.054702
converged
Fitting Repeat 4
# weights: 103
initial value 99.959590
iter 10 value 94.063816
final value 94.061524
converged
Fitting Repeat 5
# weights: 103
initial value 97.065891
final value 94.054424
converged
Fitting Repeat 1
# weights: 305
initial value 101.720739
iter 10 value 94.057140
iter 20 value 91.785823
final value 91.078937
converged
Fitting Repeat 2
# weights: 305
initial value 93.332665
iter 10 value 92.049650
iter 20 value 92.047696
iter 30 value 92.046694
iter 40 value 92.044172
iter 50 value 92.043979
iter 50 value 92.043979
final value 92.043923
converged
Fitting Repeat 3
# weights: 305
initial value 99.814609
iter 10 value 93.840920
iter 20 value 93.837106
iter 30 value 93.156088
iter 40 value 89.975481
iter 50 value 89.918311
iter 60 value 89.918242
iter 70 value 89.857570
iter 80 value 89.426286
final value 89.425682
converged
Fitting Repeat 4
# weights: 305
initial value 101.252275
iter 10 value 93.841075
iter 20 value 93.836526
iter 30 value 90.988193
iter 40 value 87.960655
iter 50 value 87.773504
iter 60 value 87.772474
iter 70 value 87.772398
iter 80 value 87.772279
iter 90 value 87.772111
final value 87.772076
converged
Fitting Repeat 5
# weights: 305
initial value 95.816284
iter 10 value 94.057995
iter 20 value 93.938552
final value 93.810675
converged
Fitting Repeat 1
# weights: 507
initial value 108.058613
iter 10 value 88.633236
iter 20 value 87.652346
iter 30 value 87.649949
iter 40 value 87.629111
iter 50 value 84.749893
iter 60 value 83.849947
iter 70 value 83.641955
iter 80 value 82.511640
iter 90 value 82.113345
iter 100 value 81.784578
final value 81.784578
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.603162
iter 10 value 94.017074
iter 20 value 93.854637
iter 30 value 88.236865
iter 40 value 87.810539
iter 50 value 87.638957
final value 87.630627
converged
Fitting Repeat 3
# weights: 507
initial value 100.179353
iter 10 value 94.036086
iter 20 value 94.028929
iter 30 value 88.096919
iter 40 value 85.263600
iter 50 value 85.247137
iter 60 value 82.969736
iter 70 value 82.933336
final value 82.932572
converged
Fitting Repeat 4
# weights: 507
initial value 95.413512
iter 10 value 94.060560
final value 94.053981
converged
Fitting Repeat 5
# weights: 507
initial value 111.617402
iter 10 value 94.061703
iter 20 value 94.053207
iter 30 value 83.251227
iter 40 value 83.136520
iter 50 value 81.518934
iter 60 value 80.315974
iter 70 value 80.136996
iter 80 value 80.131815
iter 90 value 80.131479
iter 100 value 80.113740
final value 80.113740
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.751111
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 104.309760
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.537239
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 94.830159
iter 10 value 93.206308
final value 93.135248
converged
Fitting Repeat 5
# weights: 103
initial value 96.009892
iter 10 value 94.280238
final value 94.275362
converged
Fitting Repeat 1
# weights: 305
initial value 100.983024
final value 94.046703
converged
Fitting Repeat 2
# weights: 305
initial value 114.502931
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 99.330577
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 96.097745
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 94.988592
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 99.404592
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 119.470399
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 100.911718
iter 10 value 93.486412
final value 93.486410
converged
Fitting Repeat 4
# weights: 507
initial value 100.027867
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 123.104020
final value 94.275362
converged
Fitting Repeat 1
# weights: 103
initial value 101.082477
iter 10 value 92.118023
iter 20 value 84.667529
iter 30 value 84.544100
iter 40 value 83.604381
iter 50 value 82.723688
iter 60 value 82.186420
iter 70 value 82.142661
iter 80 value 82.113897
final value 82.110999
converged
Fitting Repeat 2
# weights: 103
initial value 113.445773
iter 10 value 94.492888
iter 20 value 91.330813
iter 30 value 84.186186
iter 40 value 83.558467
iter 50 value 82.554186
iter 60 value 82.171904
iter 70 value 82.146179
final value 82.146042
converged
Fitting Repeat 3
# weights: 103
initial value 109.298252
iter 10 value 94.221954
iter 20 value 89.012829
iter 30 value 86.742700
iter 40 value 85.874039
iter 50 value 83.893932
iter 60 value 82.582067
iter 70 value 82.184567
iter 80 value 82.152983
final value 82.146901
converged
Fitting Repeat 4
# weights: 103
initial value 98.434791
iter 10 value 85.601743
iter 20 value 84.151886
iter 30 value 82.576996
iter 40 value 82.169148
final value 82.164895
converged
Fitting Repeat 5
# weights: 103
initial value 100.202619
iter 10 value 94.517701
iter 20 value 94.401490
iter 30 value 87.175198
iter 40 value 83.949665
iter 50 value 83.071553
iter 60 value 82.600419
iter 70 value 81.794739
iter 80 value 81.548905
iter 90 value 81.498199
iter 100 value 81.278944
final value 81.278944
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.763875
iter 10 value 94.436039
iter 20 value 93.578005
iter 30 value 93.359775
iter 40 value 90.760816
iter 50 value 86.105531
iter 60 value 85.409477
iter 70 value 84.184550
iter 80 value 81.395535
iter 90 value 80.699691
iter 100 value 80.188141
final value 80.188141
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 144.034214
iter 10 value 94.410219
iter 20 value 91.125554
iter 30 value 84.460322
iter 40 value 82.902504
iter 50 value 81.102388
iter 60 value 80.451485
iter 70 value 79.630041
iter 80 value 79.291458
iter 90 value 79.202201
iter 100 value 79.018780
final value 79.018780
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 108.454049
iter 10 value 94.663652
iter 20 value 94.231872
iter 30 value 87.184581
iter 40 value 83.741960
iter 50 value 82.773564
iter 60 value 82.367811
iter 70 value 82.046829
iter 80 value 81.232119
iter 90 value 80.574776
iter 100 value 79.884242
final value 79.884242
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.270078
iter 10 value 92.507414
iter 20 value 89.392580
iter 30 value 86.392428
iter 40 value 85.431168
iter 50 value 84.398298
iter 60 value 83.298360
iter 70 value 82.744283
iter 80 value 81.602337
iter 90 value 81.239615
iter 100 value 81.043981
final value 81.043981
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 116.359771
iter 10 value 94.846376
iter 20 value 94.514221
iter 30 value 85.823110
iter 40 value 84.898153
iter 50 value 83.813864
iter 60 value 82.368041
iter 70 value 81.292484
iter 80 value 81.090250
iter 90 value 80.920685
iter 100 value 80.882844
final value 80.882844
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 108.013783
iter 10 value 92.913135
iter 20 value 85.864048
iter 30 value 83.557772
iter 40 value 81.990531
iter 50 value 81.179202
iter 60 value 81.014549
iter 70 value 80.904216
iter 80 value 80.870418
iter 90 value 80.824951
iter 100 value 80.684296
final value 80.684296
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.633484
iter 10 value 96.449721
iter 20 value 87.649047
iter 30 value 83.029706
iter 40 value 82.490818
iter 50 value 80.698045
iter 60 value 80.321598
iter 70 value 79.996384
iter 80 value 79.568706
iter 90 value 79.471185
iter 100 value 79.367161
final value 79.367161
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 112.348371
iter 10 value 89.206603
iter 20 value 84.375223
iter 30 value 83.129672
iter 40 value 82.632529
iter 50 value 81.762913
iter 60 value 81.508249
iter 70 value 80.269426
iter 80 value 79.686417
iter 90 value 79.595453
iter 100 value 79.568952
final value 79.568952
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 113.027350
iter 10 value 94.706752
iter 20 value 85.905629
iter 30 value 84.442315
iter 40 value 82.046917
iter 50 value 80.878849
iter 60 value 80.542548
iter 70 value 80.111225
iter 80 value 79.802675
iter 90 value 79.382111
iter 100 value 79.194908
final value 79.194908
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.460975
iter 10 value 94.539919
iter 20 value 85.157745
iter 30 value 83.971761
iter 40 value 83.243236
iter 50 value 82.626343
iter 60 value 82.231267
iter 70 value 81.572040
iter 80 value 80.545527
iter 90 value 79.937890
iter 100 value 79.769075
final value 79.769075
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.790677
final value 94.485887
converged
Fitting Repeat 2
# weights: 103
initial value 94.834096
final value 94.486022
converged
Fitting Repeat 3
# weights: 103
initial value 99.034882
iter 10 value 94.276673
iter 20 value 94.171630
iter 30 value 94.167487
iter 40 value 94.117606
final value 94.117324
converged
Fitting Repeat 4
# weights: 103
initial value 100.661355
iter 10 value 94.485755
iter 20 value 94.295153
iter 30 value 84.484097
iter 40 value 84.483532
final value 84.483232
converged
Fitting Repeat 5
# weights: 103
initial value 99.104331
iter 10 value 94.485948
iter 20 value 94.327866
final value 94.229456
converged
Fitting Repeat 1
# weights: 305
initial value 95.324208
iter 10 value 94.489425
iter 20 value 94.484344
final value 94.484228
converged
Fitting Repeat 2
# weights: 305
initial value 97.623509
iter 10 value 93.847553
iter 20 value 84.494766
iter 30 value 83.043776
iter 40 value 82.824741
iter 50 value 82.821225
iter 60 value 82.818644
final value 82.818480
converged
Fitting Repeat 3
# weights: 305
initial value 100.813928
iter 10 value 94.488698
iter 20 value 94.314875
iter 30 value 87.225405
iter 40 value 85.878571
iter 50 value 85.756968
iter 60 value 84.976203
iter 70 value 84.975749
final value 84.975735
converged
Fitting Repeat 4
# weights: 305
initial value 99.284057
iter 10 value 94.489103
iter 20 value 94.439330
iter 30 value 87.928292
iter 40 value 84.636518
iter 50 value 84.626705
iter 60 value 82.428364
iter 70 value 80.987935
iter 80 value 80.854640
iter 90 value 80.828243
final value 80.828191
converged
Fitting Repeat 5
# weights: 305
initial value 108.130511
iter 10 value 93.875445
iter 20 value 93.814191
iter 30 value 93.806564
iter 40 value 93.438137
iter 50 value 93.289855
iter 60 value 93.237191
iter 70 value 93.236341
iter 80 value 93.229652
iter 90 value 87.538301
iter 100 value 87.281076
final value 87.281076
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.344144
iter 10 value 94.426105
iter 20 value 93.277266
iter 30 value 91.747087
iter 40 value 85.169496
iter 50 value 84.164836
iter 60 value 83.983958
iter 70 value 83.959336
iter 80 value 83.406221
iter 90 value 83.212296
iter 100 value 83.207561
final value 83.207561
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.150887
iter 10 value 94.237754
iter 20 value 94.236736
iter 30 value 94.230397
iter 40 value 94.230152
iter 50 value 94.229297
final value 94.228975
converged
Fitting Repeat 3
# weights: 507
initial value 99.356442
iter 10 value 94.497157
iter 20 value 94.488797
iter 30 value 94.476943
iter 40 value 94.279986
iter 50 value 94.240722
iter 60 value 93.974110
final value 93.973796
converged
Fitting Repeat 4
# weights: 507
initial value 113.978014
iter 10 value 93.605671
iter 20 value 93.583875
iter 30 value 93.417081
iter 40 value 93.098051
final value 92.955535
converged
Fitting Repeat 5
# weights: 507
initial value 103.374720
iter 10 value 94.283694
iter 20 value 94.276302
iter 30 value 89.465696
iter 40 value 84.223361
iter 50 value 84.036538
iter 60 value 83.962961
iter 70 value 82.120790
iter 80 value 79.991371
iter 90 value 77.999604
iter 100 value 77.858319
final value 77.858319
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.003896
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 100.151983
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 102.610671
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 106.763833
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 103.409443
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 97.717440
iter 10 value 92.361781
final value 90.944892
converged
Fitting Repeat 2
# weights: 305
initial value 103.874159
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 99.802934
final value 94.052448
converged
Fitting Repeat 4
# weights: 305
initial value 105.453829
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 94.667479
iter 10 value 91.272693
iter 20 value 90.945527
final value 90.944891
converged
Fitting Repeat 1
# weights: 507
initial value 101.407044
final value 94.038251
converged
Fitting Repeat 2
# weights: 507
initial value 104.965211
iter 10 value 93.206689
iter 20 value 91.712982
iter 30 value 91.228027
iter 40 value 88.656415
iter 50 value 84.396004
iter 60 value 84.104581
iter 70 value 84.066908
iter 80 value 84.063220
iter 90 value 84.063018
iter 100 value 84.062992
final value 84.062992
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 96.437908
final value 94.038009
converged
Fitting Repeat 4
# weights: 507
initial value 103.238312
iter 10 value 92.475674
iter 20 value 92.435195
final value 92.369872
converged
Fitting Repeat 5
# weights: 507
initial value 102.249581
iter 10 value 94.038252
iter 10 value 94.038251
iter 10 value 94.038251
final value 94.038251
converged
Fitting Repeat 1
# weights: 103
initial value 97.171228
iter 10 value 94.009404
iter 20 value 91.062186
iter 30 value 89.242805
iter 40 value 88.979803
iter 50 value 87.865143
iter 60 value 87.735710
iter 70 value 86.898870
iter 80 value 85.354724
iter 90 value 85.271633
final value 85.271483
converged
Fitting Repeat 2
# weights: 103
initial value 101.073120
iter 10 value 94.021223
iter 20 value 91.794891
iter 30 value 87.534519
iter 40 value 87.090823
iter 50 value 85.076996
iter 60 value 84.453387
iter 70 value 84.439365
final value 84.439329
converged
Fitting Repeat 3
# weights: 103
initial value 98.889730
iter 10 value 94.131630
iter 20 value 94.046714
iter 30 value 92.159287
iter 40 value 91.003222
iter 50 value 90.873916
iter 60 value 90.784982
iter 70 value 90.752405
iter 80 value 84.645311
iter 90 value 83.617030
iter 100 value 83.130070
final value 83.130070
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 107.622498
iter 10 value 94.042057
iter 20 value 88.702763
iter 30 value 88.187598
iter 40 value 88.086172
iter 50 value 87.511362
iter 60 value 87.227869
final value 87.227679
converged
Fitting Repeat 5
# weights: 103
initial value 97.987510
iter 10 value 93.952730
iter 20 value 91.854857
iter 30 value 87.181760
iter 40 value 86.806123
iter 50 value 86.563256
iter 60 value 83.719925
iter 70 value 83.669056
iter 80 value 83.665729
iter 90 value 83.665530
final value 83.665514
converged
Fitting Repeat 1
# weights: 305
initial value 107.706347
iter 10 value 94.075287
iter 20 value 93.728826
iter 30 value 93.272867
iter 40 value 92.783408
iter 50 value 90.853193
iter 60 value 90.730565
iter 70 value 89.942091
iter 80 value 87.070061
iter 90 value 86.243962
iter 100 value 84.692750
final value 84.692750
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.457489
iter 10 value 94.063220
iter 20 value 92.522426
iter 30 value 88.461989
iter 40 value 88.172445
iter 50 value 87.239075
iter 60 value 85.684638
iter 70 value 84.870341
iter 80 value 84.407992
iter 90 value 83.251131
iter 100 value 82.617614
final value 82.617614
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.463176
iter 10 value 97.113111
iter 20 value 87.473044
iter 30 value 85.827395
iter 40 value 84.779489
iter 50 value 84.118543
iter 60 value 83.057902
iter 70 value 82.536047
iter 80 value 82.361959
iter 90 value 82.182108
iter 100 value 82.050668
final value 82.050668
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.293585
iter 10 value 90.617424
iter 20 value 86.585465
iter 30 value 83.993910
iter 40 value 83.816387
iter 50 value 83.681802
iter 60 value 83.487341
iter 70 value 83.428497
iter 80 value 83.327427
iter 90 value 83.175971
iter 100 value 82.840832
final value 82.840832
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.022923
iter 10 value 93.508095
iter 20 value 88.317238
iter 30 value 85.222962
iter 40 value 83.322668
iter 50 value 83.026984
iter 60 value 82.661440
iter 70 value 82.042307
iter 80 value 81.889490
iter 90 value 81.778205
iter 100 value 81.760597
final value 81.760597
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 114.858030
iter 10 value 101.166347
iter 20 value 88.683120
iter 30 value 87.533861
iter 40 value 86.926818
iter 50 value 85.334838
iter 60 value 82.695376
iter 70 value 82.178794
iter 80 value 81.974903
iter 90 value 81.919514
iter 100 value 81.648466
final value 81.648466
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 119.371437
iter 10 value 94.239513
iter 20 value 90.028820
iter 30 value 85.566340
iter 40 value 82.915778
iter 50 value 82.636349
iter 60 value 81.745440
iter 70 value 81.487348
iter 80 value 81.463305
iter 90 value 81.436129
iter 100 value 81.346728
final value 81.346728
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 123.893560
iter 10 value 94.236040
iter 20 value 92.247729
iter 30 value 92.035244
iter 40 value 89.038061
iter 50 value 88.381683
iter 60 value 84.934849
iter 70 value 84.255024
iter 80 value 83.054674
iter 90 value 82.077371
iter 100 value 81.724165
final value 81.724165
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 116.042987
iter 10 value 95.382739
iter 20 value 94.012300
iter 30 value 91.019786
iter 40 value 85.400138
iter 50 value 84.049473
iter 60 value 82.515181
iter 70 value 81.817400
iter 80 value 81.675718
iter 90 value 81.615079
iter 100 value 81.451031
final value 81.451031
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.214957
iter 10 value 92.087235
iter 20 value 85.581701
iter 30 value 83.473473
iter 40 value 83.275918
iter 50 value 82.951293
iter 60 value 82.597824
iter 70 value 82.241525
iter 80 value 82.019546
iter 90 value 81.689959
iter 100 value 81.555502
final value 81.555502
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.031055
final value 94.054621
converged
Fitting Repeat 2
# weights: 103
initial value 103.887034
final value 94.054586
converged
Fitting Repeat 3
# weights: 103
initial value 109.710038
final value 94.054445
converged
Fitting Repeat 4
# weights: 103
initial value 98.877290
final value 94.054530
converged
Fitting Repeat 5
# weights: 103
initial value 103.865796
iter 10 value 94.039885
iter 20 value 94.038342
iter 30 value 90.993315
final value 90.945703
converged
Fitting Repeat 1
# weights: 305
initial value 96.231302
iter 10 value 94.042758
iter 20 value 94.038369
final value 94.038323
converged
Fitting Repeat 2
# weights: 305
initial value 96.978235
iter 10 value 94.058057
iter 20 value 94.054541
iter 30 value 94.046108
iter 40 value 94.044735
iter 50 value 93.532462
iter 60 value 93.050390
iter 70 value 93.030917
final value 93.030764
converged
Fitting Repeat 3
# weights: 305
initial value 113.381542
iter 10 value 94.058932
iter 20 value 94.054206
iter 30 value 89.562120
iter 40 value 87.945479
iter 50 value 87.944753
iter 60 value 87.943353
iter 70 value 87.055341
iter 80 value 83.701494
iter 90 value 82.277620
iter 100 value 81.970660
final value 81.970660
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 96.025293
iter 10 value 94.057682
iter 20 value 94.053188
iter 30 value 92.268835
iter 40 value 87.941980
iter 50 value 86.865195
iter 60 value 86.714490
final value 86.713930
converged
Fitting Repeat 5
# weights: 305
initial value 98.134783
iter 10 value 94.056779
iter 20 value 94.043672
iter 30 value 94.042735
iter 40 value 94.039413
iter 50 value 86.788748
iter 60 value 86.523908
final value 86.523717
converged
Fitting Repeat 1
# weights: 507
initial value 106.682775
iter 10 value 93.366123
iter 20 value 92.329015
iter 30 value 91.413536
iter 40 value 91.412844
iter 50 value 91.408024
iter 60 value 91.349993
iter 70 value 91.345295
iter 80 value 91.344344
iter 90 value 91.343425
iter 100 value 91.342033
final value 91.342033
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.602633
iter 10 value 94.046028
iter 20 value 94.039328
iter 30 value 93.848425
iter 40 value 93.823846
final value 93.823698
converged
Fitting Repeat 3
# weights: 507
initial value 111.807268
iter 10 value 93.541402
iter 20 value 92.974041
iter 30 value 86.506169
iter 40 value 86.346678
iter 50 value 84.123196
iter 60 value 84.077139
iter 70 value 84.074908
iter 80 value 84.073816
iter 90 value 83.620982
iter 100 value 83.465931
final value 83.465931
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 102.150313
iter 10 value 88.407719
iter 20 value 86.583861
iter 30 value 86.476656
iter 40 value 86.384552
iter 50 value 86.371818
iter 60 value 86.353514
iter 70 value 85.916722
iter 80 value 85.889062
iter 90 value 85.792716
iter 100 value 85.638448
final value 85.638448
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 99.061670
iter 10 value 93.541597
iter 20 value 90.116395
iter 30 value 88.077291
iter 40 value 88.076507
iter 50 value 87.852131
iter 60 value 87.776406
final value 87.776320
converged
Fitting Repeat 1
# weights: 507
initial value 140.211372
iter 10 value 118.358018
iter 20 value 118.048681
iter 30 value 117.758660
iter 40 value 117.390189
iter 50 value 114.452972
iter 60 value 112.549984
iter 70 value 111.272599
iter 80 value 109.384781
iter 90 value 105.718372
iter 100 value 104.519307
final value 104.519307
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 136.407219
iter 10 value 115.783647
iter 20 value 108.522274
iter 30 value 107.082902
iter 40 value 106.061619
iter 50 value 105.159047
iter 60 value 104.294918
iter 70 value 103.167105
iter 80 value 102.765950
iter 90 value 102.619059
iter 100 value 102.340702
final value 102.340702
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 143.236802
iter 10 value 113.836025
iter 20 value 109.402817
iter 30 value 106.960988
iter 40 value 105.905113
iter 50 value 105.125114
iter 60 value 103.742578
iter 70 value 102.899059
iter 80 value 102.794026
iter 90 value 102.089146
iter 100 value 101.914013
final value 101.914013
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 132.771431
iter 10 value 119.781814
iter 20 value 110.788352
iter 30 value 107.935964
iter 40 value 106.306046
iter 50 value 105.513527
iter 60 value 103.762947
iter 70 value 102.230513
iter 80 value 101.996414
iter 90 value 101.661738
iter 100 value 101.235304
final value 101.235304
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 139.251481
iter 10 value 117.801571
iter 20 value 109.580354
iter 30 value 106.564344
iter 40 value 105.556790
iter 50 value 105.322797
iter 60 value 105.028205
iter 70 value 104.097916
iter 80 value 102.492674
iter 90 value 101.928185
iter 100 value 101.399963
final value 101.399963
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 Dec 22 00:12:25 2025
***********************************************
Number of test functions: 7
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7
Number of errors: 0
Number of failures: 0
Warning messages:
1: `repeats` has no meaning for this resampling method.
2: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
41.211 1.171 85.781
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 32.708 | 0.623 | 33.389 | |
| FreqInteractors | 0.440 | 0.031 | 0.472 | |
| calculateAAC | 0.030 | 0.002 | 0.033 | |
| calculateAutocor | 0.317 | 0.015 | 0.332 | |
| calculateCTDC | 0.075 | 0.000 | 0.074 | |
| calculateCTDD | 0.455 | 0.003 | 0.458 | |
| calculateCTDT | 0.137 | 0.001 | 0.138 | |
| calculateCTriad | 0.384 | 0.008 | 0.391 | |
| calculateDC | 0.088 | 0.007 | 0.095 | |
| calculateF | 0.300 | 0.001 | 0.301 | |
| calculateKSAAP | 0.100 | 0.007 | 0.107 | |
| calculateQD_Sm | 1.802 | 0.030 | 1.832 | |
| calculateTC | 1.514 | 0.139 | 1.653 | |
| calculateTC_Sm | 0.295 | 0.005 | 0.300 | |
| corr_plot | 34.723 | 0.582 | 35.377 | |
| enrichfindP | 0.576 | 0.039 | 15.471 | |
| enrichfind_hp | 0.063 | 0.001 | 1.075 | |
| enrichplot | 0.480 | 0.004 | 0.483 | |
| filter_missing_values | 0.000 | 0.001 | 0.001 | |
| getFASTA | 0.439 | 0.007 | 7.148 | |
| getHPI | 0.001 | 0.000 | 0.001 | |
| get_negativePPI | 0.001 | 0.001 | 0.002 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.002 | 0.001 | 0.001 | |
| plotPPI | 0.083 | 0.002 | 0.085 | |
| pred_ensembel | 12.988 | 0.119 | 11.717 | |
| var_imp | 33.627 | 0.344 | 34.012 | |