| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2025-12-20 11:34 -0500 (Sat, 20 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" | 4875 |
| 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: 2025-12-20 00:07:17 -0500 (Sat, 20 Dec 2025) |
| EndedAt: 2025-12-20 00:22:39 -0500 (Sat, 20 Dec 2025) |
| EllapsedTime: 921.3 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 34.175 0.381 34.591
var_imp 33.463 0.382 33.904
FSmethod 33.150 0.637 33.811
pred_ensembel 12.930 0.107 11.662
enrichfindP 0.542 0.036 14.688
getFASTA 0.410 0.008 6.469
* 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 100.865107
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 103.009544
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.593606
final value 94.038251
converged
Fitting Repeat 4
# weights: 103
initial value 101.759149
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 100.618909
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 111.943997
final value 94.038252
converged
Fitting Repeat 2
# weights: 305
initial value 110.502686
iter 10 value 93.905199
iter 20 value 93.881226
iter 20 value 93.881226
iter 20 value 93.881226
final value 93.881226
converged
Fitting Repeat 3
# weights: 305
initial value 107.094243
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 102.877412
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 97.294812
iter 10 value 93.962989
iter 20 value 93.571741
final value 93.571532
converged
Fitting Repeat 1
# weights: 507
initial value 114.921803
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 92.575101
iter 10 value 86.268667
final value 86.268064
converged
Fitting Repeat 3
# weights: 507
initial value 128.911165
final value 94.052909
converged
Fitting Repeat 4
# weights: 507
initial value 100.057733
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 107.811289
iter 10 value 93.994907
iter 20 value 92.388385
iter 30 value 86.271275
final value 86.264140
converged
Fitting Repeat 1
# weights: 103
initial value 109.123601
iter 10 value 94.147526
iter 20 value 93.894644
iter 30 value 91.808238
iter 40 value 91.251176
iter 50 value 87.628231
iter 60 value 87.125097
iter 70 value 86.652060
iter 80 value 84.424074
iter 90 value 84.368000
final value 84.367144
converged
Fitting Repeat 2
# weights: 103
initial value 100.200886
iter 10 value 92.869905
iter 20 value 89.796485
iter 30 value 87.624723
iter 40 value 86.992689
iter 50 value 86.594918
final value 86.593700
converged
Fitting Repeat 3
# weights: 103
initial value 97.838149
iter 10 value 93.962582
iter 20 value 93.825378
iter 30 value 88.350816
iter 40 value 85.588544
iter 50 value 84.182529
iter 60 value 83.671759
iter 70 value 83.634900
iter 80 value 83.574864
iter 90 value 83.214440
iter 100 value 83.108524
final value 83.108524
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 100.252194
iter 10 value 94.048029
iter 20 value 93.131008
iter 30 value 88.212768
iter 40 value 87.242393
iter 50 value 86.758505
iter 60 value 84.922169
iter 70 value 84.523034
iter 80 value 83.701856
iter 90 value 83.336789
iter 100 value 83.108318
final value 83.108318
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 100.764388
iter 10 value 93.291654
iter 20 value 88.335380
iter 30 value 85.771351
iter 40 value 85.427513
iter 50 value 85.285333
iter 60 value 85.279521
final value 85.279515
converged
Fitting Repeat 1
# weights: 305
initial value 106.150004
iter 10 value 94.158676
iter 20 value 93.647646
iter 30 value 93.070662
iter 40 value 88.844195
iter 50 value 85.645363
iter 60 value 84.766223
iter 70 value 84.507560
iter 80 value 84.130556
iter 90 value 83.551591
iter 100 value 82.778050
final value 82.778050
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 115.918310
iter 10 value 95.941929
iter 20 value 93.916527
iter 30 value 87.944965
iter 40 value 86.848377
iter 50 value 86.079059
iter 60 value 84.509896
iter 70 value 82.821828
iter 80 value 82.327466
iter 90 value 81.835265
iter 100 value 81.761234
final value 81.761234
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.392647
iter 10 value 91.523587
iter 20 value 90.109867
iter 30 value 84.529943
iter 40 value 82.999944
iter 50 value 82.643086
iter 60 value 82.381107
iter 70 value 82.330525
iter 80 value 82.318611
iter 90 value 82.248089
iter 100 value 82.119631
final value 82.119631
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 125.756175
iter 10 value 94.240696
iter 20 value 89.132509
iter 30 value 86.310902
iter 40 value 84.071743
iter 50 value 82.965994
iter 60 value 82.534399
iter 70 value 82.091478
iter 80 value 81.997252
iter 90 value 81.921580
iter 100 value 81.793182
final value 81.793182
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.491844
iter 10 value 93.872081
iter 20 value 87.883430
iter 30 value 86.389148
iter 40 value 84.512735
iter 50 value 84.258580
iter 60 value 84.168685
iter 70 value 84.153982
iter 80 value 84.144839
iter 90 value 84.126202
iter 100 value 84.106345
final value 84.106345
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.353872
iter 10 value 94.120475
iter 20 value 93.858206
iter 30 value 91.182374
iter 40 value 87.208504
iter 50 value 86.398456
iter 60 value 86.165203
iter 70 value 86.111523
iter 80 value 86.086740
iter 90 value 85.815541
iter 100 value 84.543673
final value 84.543673
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 118.018363
iter 10 value 94.138665
iter 20 value 93.667106
iter 30 value 90.702421
iter 40 value 90.092762
iter 50 value 87.989729
iter 60 value 86.947333
iter 70 value 84.773224
iter 80 value 84.069019
iter 90 value 83.833411
iter 100 value 83.158974
final value 83.158974
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.218616
iter 10 value 94.048422
iter 20 value 89.971069
iter 30 value 88.923747
iter 40 value 88.212906
iter 50 value 87.506385
iter 60 value 85.947849
iter 70 value 85.316488
iter 80 value 84.929326
iter 90 value 84.164223
iter 100 value 83.693120
final value 83.693120
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 113.231262
iter 10 value 94.793932
iter 20 value 89.743660
iter 30 value 86.155274
iter 40 value 84.687352
iter 50 value 84.332963
iter 60 value 84.020846
iter 70 value 83.962777
iter 80 value 83.944867
iter 90 value 83.671929
iter 100 value 82.917836
final value 82.917836
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.244978
iter 10 value 94.299181
iter 20 value 87.181028
iter 30 value 86.751492
iter 40 value 85.582331
iter 50 value 85.385601
iter 60 value 83.903313
iter 70 value 82.418616
iter 80 value 82.028634
iter 90 value 81.913034
iter 100 value 81.659991
final value 81.659991
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.228227
iter 10 value 94.039700
iter 20 value 94.038349
final value 94.038270
converged
Fitting Repeat 2
# weights: 103
initial value 102.518268
final value 94.054399
converged
Fitting Repeat 3
# weights: 103
initial value 98.378640
final value 94.054790
converged
Fitting Repeat 4
# weights: 103
initial value 102.092402
iter 10 value 94.054708
iter 20 value 94.050331
iter 30 value 94.040186
iter 40 value 94.039700
iter 50 value 94.039423
iter 60 value 94.038992
iter 70 value 94.038312
final value 94.038261
converged
Fitting Repeat 5
# weights: 103
initial value 105.315731
final value 94.054296
converged
Fitting Repeat 1
# weights: 305
initial value 116.894499
iter 10 value 94.057266
iter 20 value 94.053053
final value 94.053019
converged
Fitting Repeat 2
# weights: 305
initial value 108.999469
iter 10 value 93.814932
iter 20 value 93.810292
final value 93.810286
converged
Fitting Repeat 3
# weights: 305
initial value 107.548087
iter 10 value 90.531749
iter 20 value 86.254215
iter 30 value 86.203509
iter 40 value 86.022704
iter 50 value 86.018741
iter 60 value 85.998335
iter 70 value 84.923990
iter 80 value 84.701085
final value 84.700975
converged
Fitting Repeat 4
# weights: 305
initial value 95.963604
iter 10 value 94.057322
iter 20 value 94.039471
iter 30 value 91.431193
iter 40 value 91.413402
iter 50 value 87.379611
iter 60 value 87.189582
iter 70 value 87.119956
iter 80 value 87.112689
iter 90 value 87.107951
iter 100 value 87.099401
final value 87.099401
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.321096
iter 10 value 94.057434
iter 20 value 94.038580
iter 30 value 91.402213
iter 40 value 89.643166
iter 50 value 89.640043
iter 60 value 89.509633
iter 70 value 89.470729
iter 80 value 87.946863
iter 90 value 87.593817
iter 100 value 87.590343
final value 87.590343
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.473692
iter 10 value 93.952952
iter 20 value 93.951080
iter 30 value 90.855150
iter 40 value 86.066678
iter 50 value 86.019519
iter 60 value 86.019136
final value 86.018226
converged
Fitting Repeat 2
# weights: 507
initial value 105.476804
iter 10 value 93.807711
iter 20 value 93.802728
final value 93.801707
converged
Fitting Repeat 3
# weights: 507
initial value 99.625760
iter 10 value 93.808978
iter 20 value 93.803949
iter 30 value 87.397996
iter 40 value 86.708971
iter 50 value 86.369194
iter 60 value 85.548829
iter 70 value 85.315304
iter 80 value 85.315046
iter 90 value 85.292510
final value 85.292243
converged
Fitting Repeat 4
# weights: 507
initial value 97.731943
iter 10 value 94.046229
iter 20 value 94.040179
final value 94.040112
converged
Fitting Repeat 5
# weights: 507
initial value 103.940429
iter 10 value 88.545112
iter 20 value 87.947610
iter 30 value 87.142430
iter 40 value 86.497958
iter 50 value 86.494131
iter 50 value 86.494131
final value 86.494131
converged
Fitting Repeat 1
# weights: 103
initial value 98.903925
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.467738
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 103.329076
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.148750
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.613485
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 95.596576
iter 10 value 93.540495
final value 93.540410
converged
Fitting Repeat 2
# weights: 305
initial value 94.502612
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 109.907921
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 106.063591
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 101.290178
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 129.508516
iter 10 value 95.664707
iter 20 value 87.797065
final value 87.794120
converged
Fitting Repeat 2
# weights: 507
initial value 108.032404
iter 10 value 93.579111
final value 93.558233
converged
Fitting Repeat 3
# weights: 507
initial value 95.589598
iter 10 value 93.772975
final value 93.772973
converged
Fitting Repeat 4
# weights: 507
initial value 102.938082
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 98.954062
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 111.167062
iter 10 value 94.293787
iter 20 value 90.442567
iter 30 value 89.177742
iter 40 value 83.409576
iter 50 value 82.837922
iter 60 value 82.292965
iter 70 value 80.910676
iter 80 value 80.522051
final value 80.513414
converged
Fitting Repeat 2
# weights: 103
initial value 108.769249
iter 10 value 94.075459
iter 20 value 92.594291
iter 30 value 87.768885
iter 40 value 84.677618
iter 50 value 83.079670
iter 60 value 82.929279
final value 82.928646
converged
Fitting Repeat 3
# weights: 103
initial value 98.098467
iter 10 value 94.486947
iter 20 value 93.898722
iter 30 value 93.598077
iter 40 value 93.529364
iter 50 value 93.529291
iter 50 value 93.529290
iter 50 value 93.529290
final value 93.529290
converged
Fitting Repeat 4
# weights: 103
initial value 101.240286
iter 10 value 94.392754
iter 20 value 92.072190
iter 30 value 91.758768
iter 40 value 90.844035
iter 50 value 85.250622
iter 60 value 81.967218
iter 70 value 81.896023
iter 80 value 81.186287
iter 90 value 80.827822
iter 100 value 80.514645
final value 80.514645
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 104.604220
iter 10 value 94.472204
iter 20 value 86.783734
iter 30 value 85.418448
iter 40 value 85.004190
iter 50 value 84.019873
iter 60 value 83.154304
iter 70 value 82.226044
iter 80 value 81.915849
iter 90 value 81.179360
iter 100 value 81.133358
final value 81.133358
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 102.842399
iter 10 value 95.287939
iter 20 value 94.467006
iter 30 value 93.822309
iter 40 value 91.783654
iter 50 value 89.347465
iter 60 value 87.531080
iter 70 value 81.597558
iter 80 value 80.427822
iter 90 value 79.854745
iter 100 value 79.596919
final value 79.596919
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.928009
iter 10 value 94.418435
iter 20 value 93.723001
iter 30 value 93.397848
iter 40 value 85.779979
iter 50 value 85.149382
iter 60 value 84.611419
iter 70 value 84.280177
iter 80 value 84.013999
iter 90 value 83.764384
iter 100 value 83.592816
final value 83.592816
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 111.407101
iter 10 value 94.432087
iter 20 value 88.409069
iter 30 value 87.862827
iter 40 value 82.264175
iter 50 value 80.722042
iter 60 value 79.723262
iter 70 value 79.556517
iter 80 value 79.510131
iter 90 value 79.464876
iter 100 value 79.363522
final value 79.363522
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.373116
iter 10 value 94.403814
iter 20 value 91.210957
iter 30 value 90.042613
iter 40 value 89.662589
iter 50 value 87.834787
iter 60 value 85.994581
iter 70 value 82.809853
iter 80 value 81.574985
iter 90 value 80.492682
iter 100 value 80.297175
final value 80.297175
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 128.074728
iter 10 value 94.651641
iter 20 value 93.862469
iter 30 value 87.442913
iter 40 value 84.185543
iter 50 value 82.974821
iter 60 value 82.752079
iter 70 value 82.718945
iter 80 value 82.704284
iter 90 value 81.961624
iter 100 value 81.111808
final value 81.111808
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 114.963860
iter 10 value 92.441106
iter 20 value 84.929323
iter 30 value 84.771350
iter 40 value 83.693438
iter 50 value 83.291103
iter 60 value 83.126528
iter 70 value 82.854770
iter 80 value 81.167090
iter 90 value 80.042711
iter 100 value 79.749864
final value 79.749864
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 101.866646
iter 10 value 89.747962
iter 20 value 88.521029
iter 30 value 86.596226
iter 40 value 83.196975
iter 50 value 83.052518
iter 60 value 82.778736
iter 70 value 82.631603
iter 80 value 82.149397
iter 90 value 80.830096
iter 100 value 80.171751
final value 80.171751
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 117.733354
iter 10 value 93.939462
iter 20 value 88.510541
iter 30 value 85.914989
iter 40 value 83.770701
iter 50 value 81.314875
iter 60 value 81.015678
iter 70 value 80.732592
iter 80 value 80.365129
iter 90 value 80.258600
iter 100 value 80.184636
final value 80.184636
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 116.990090
iter 10 value 94.311983
iter 20 value 93.097810
iter 30 value 86.060617
iter 40 value 84.764994
iter 50 value 82.526750
iter 60 value 82.153793
iter 70 value 81.904843
iter 80 value 80.393502
iter 90 value 79.562775
iter 100 value 79.361151
final value 79.361151
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 126.426953
iter 10 value 94.561743
iter 20 value 84.416428
iter 30 value 81.953084
iter 40 value 81.658363
iter 50 value 80.958941
iter 60 value 80.308264
iter 70 value 79.923133
iter 80 value 79.524222
iter 90 value 79.104718
iter 100 value 79.025439
final value 79.025439
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.403710
iter 10 value 94.485883
iter 20 value 94.484276
final value 94.484216
converged
Fitting Repeat 2
# weights: 103
initial value 97.074289
iter 10 value 93.775338
iter 20 value 93.775066
iter 30 value 92.923516
iter 40 value 90.703516
iter 50 value 85.974378
iter 60 value 85.672576
iter 70 value 84.983073
iter 80 value 84.887254
final value 84.886846
converged
Fitting Repeat 3
# weights: 103
initial value 105.328935
iter 10 value 94.485925
final value 94.484213
converged
Fitting Repeat 4
# weights: 103
initial value 102.878225
iter 10 value 93.559935
iter 20 value 92.624534
iter 30 value 83.878885
iter 40 value 83.875956
iter 50 value 83.875360
iter 60 value 83.868114
iter 70 value 83.657190
final value 83.657117
converged
Fitting Repeat 5
# weights: 103
initial value 100.547722
final value 94.485776
converged
Fitting Repeat 1
# weights: 305
initial value 105.906814
iter 10 value 91.956453
iter 20 value 91.512038
iter 30 value 91.215802
iter 40 value 91.190980
iter 50 value 87.437542
iter 60 value 84.638264
iter 70 value 83.941047
iter 80 value 83.320404
final value 83.320038
converged
Fitting Repeat 2
# weights: 305
initial value 95.573200
iter 10 value 93.778655
iter 20 value 93.766807
iter 30 value 93.483982
iter 40 value 93.410025
final value 93.409827
converged
Fitting Repeat 3
# weights: 305
initial value 104.558974
iter 10 value 94.488543
iter 20 value 93.430178
final value 93.409764
converged
Fitting Repeat 4
# weights: 305
initial value 104.666570
iter 10 value 93.778842
iter 20 value 93.777993
iter 30 value 93.723119
iter 40 value 93.136404
iter 50 value 84.600654
iter 60 value 84.565667
iter 70 value 84.320861
iter 80 value 84.127649
iter 90 value 84.127456
iter 100 value 84.127369
final value 84.127369
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 110.826262
iter 10 value 93.778253
iter 20 value 93.777396
iter 30 value 93.278354
iter 40 value 86.218456
iter 50 value 85.307025
iter 60 value 84.145801
iter 70 value 83.928598
iter 80 value 83.851621
iter 90 value 83.826874
iter 100 value 83.814521
final value 83.814521
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 95.985631
iter 10 value 94.491143
iter 20 value 86.578070
iter 30 value 86.443901
iter 40 value 86.363221
iter 50 value 83.398280
iter 60 value 83.012546
iter 70 value 82.783930
final value 82.783786
converged
Fitting Repeat 2
# weights: 507
initial value 133.278207
iter 10 value 94.491470
iter 20 value 94.421596
iter 30 value 89.012874
iter 40 value 82.817575
iter 50 value 80.246648
iter 60 value 80.206917
iter 70 value 80.048576
iter 80 value 80.045774
iter 90 value 80.043750
iter 100 value 80.040348
final value 80.040348
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 101.889822
iter 10 value 91.945536
iter 20 value 87.893225
iter 30 value 86.371717
iter 40 value 86.143278
iter 50 value 86.038803
iter 60 value 86.033363
iter 70 value 86.013389
iter 80 value 86.012955
final value 86.012940
converged
Fitting Repeat 4
# weights: 507
initial value 104.472802
iter 10 value 93.822518
iter 20 value 93.801472
iter 30 value 93.570906
iter 40 value 93.570207
iter 50 value 93.409686
final value 93.409483
converged
Fitting Repeat 5
# weights: 507
initial value 99.826565
iter 10 value 94.319866
iter 20 value 93.998224
iter 30 value 90.483245
iter 40 value 87.941874
iter 50 value 87.941404
iter 60 value 87.940259
final value 87.940221
converged
Fitting Repeat 1
# weights: 103
initial value 96.729595
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 111.856858
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 104.190577
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.712159
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 97.595701
final value 94.466823
converged
Fitting Repeat 1
# weights: 305
initial value 102.756243
iter 10 value 94.466842
final value 94.466823
converged
Fitting Repeat 2
# weights: 305
initial value 104.929100
iter 10 value 94.276328
final value 94.276324
converged
Fitting Repeat 3
# weights: 305
initial value 99.949993
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 98.468912
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 108.543455
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 95.850658
iter 10 value 86.115828
iter 20 value 85.833499
final value 85.833463
converged
Fitting Repeat 2
# weights: 507
initial value 96.207608
final value 94.484137
converged
Fitting Repeat 3
# weights: 507
initial value 96.470653
iter 10 value 91.292511
iter 20 value 91.155632
iter 30 value 91.136879
iter 40 value 82.477200
iter 50 value 81.917538
iter 60 value 81.850422
iter 70 value 81.782132
iter 80 value 81.627681
iter 90 value 81.626335
final value 81.626315
converged
Fitting Repeat 4
# weights: 507
initial value 129.374080
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 107.380886
iter 10 value 92.649884
iter 20 value 83.882669
iter 30 value 82.831246
iter 40 value 82.819517
final value 82.819239
converged
Fitting Repeat 1
# weights: 103
initial value 106.483680
iter 10 value 94.438099
iter 20 value 88.889211
iter 30 value 85.563621
iter 40 value 84.105305
iter 50 value 83.904176
final value 83.903828
converged
Fitting Repeat 2
# weights: 103
initial value 96.637503
iter 10 value 94.487397
iter 20 value 94.361580
iter 30 value 92.491760
iter 40 value 92.355668
iter 50 value 92.101101
iter 60 value 91.979427
iter 70 value 91.438693
iter 80 value 91.200780
iter 90 value 91.144719
iter 90 value 91.144719
iter 90 value 91.144719
final value 91.144719
converged
Fitting Repeat 3
# weights: 103
initial value 97.691114
iter 10 value 92.175758
iter 20 value 85.084948
iter 30 value 83.808995
iter 40 value 83.422355
iter 50 value 83.175582
final value 83.175513
converged
Fitting Repeat 4
# weights: 103
initial value 101.067363
iter 10 value 94.477935
iter 20 value 92.635395
iter 30 value 91.856937
iter 40 value 91.829765
iter 50 value 85.784578
iter 60 value 85.131222
iter 70 value 84.636364
iter 80 value 83.631274
iter 90 value 83.176189
final value 83.175513
converged
Fitting Repeat 5
# weights: 103
initial value 99.969338
iter 10 value 92.598309
iter 20 value 89.801652
iter 30 value 89.350397
iter 40 value 88.152132
iter 50 value 86.970553
iter 60 value 86.337534
iter 70 value 83.559234
iter 80 value 83.499911
iter 90 value 83.484768
final value 83.480867
converged
Fitting Repeat 1
# weights: 305
initial value 102.245594
iter 10 value 94.504290
iter 20 value 85.586127
iter 30 value 84.906750
iter 40 value 84.757790
iter 50 value 84.122697
iter 60 value 80.682672
iter 70 value 80.085101
iter 80 value 79.777745
iter 90 value 79.573323
iter 100 value 79.469136
final value 79.469136
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.399850
iter 10 value 94.383910
iter 20 value 87.578965
iter 30 value 85.693634
iter 40 value 83.686571
iter 50 value 83.352755
iter 60 value 82.368308
iter 70 value 80.168513
iter 80 value 79.692447
iter 90 value 79.307777
iter 100 value 79.195474
final value 79.195474
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 115.250797
iter 10 value 94.533453
iter 20 value 94.412532
iter 30 value 90.699872
iter 40 value 89.670285
iter 50 value 87.369987
iter 60 value 84.505316
iter 70 value 83.531726
iter 80 value 81.982791
iter 90 value 80.622098
iter 100 value 79.322220
final value 79.322220
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 119.745733
iter 10 value 94.449003
iter 20 value 89.810526
iter 30 value 87.990704
iter 40 value 86.843316
iter 50 value 84.189374
iter 60 value 82.136019
iter 70 value 81.484457
iter 80 value 80.569833
iter 90 value 80.074103
iter 100 value 79.653216
final value 79.653216
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 132.523406
iter 10 value 94.456140
iter 20 value 89.332412
iter 30 value 84.145146
iter 40 value 83.750928
iter 50 value 83.522002
iter 60 value 82.706844
iter 70 value 80.583757
iter 80 value 80.039810
iter 90 value 79.929014
iter 100 value 79.397470
final value 79.397470
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 114.701817
iter 10 value 99.567036
iter 20 value 94.797706
iter 30 value 94.443458
iter 40 value 91.812101
iter 50 value 82.400675
iter 60 value 80.623282
iter 70 value 79.912014
iter 80 value 79.193658
iter 90 value 79.046227
iter 100 value 78.834601
final value 78.834601
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.293283
iter 10 value 94.616550
iter 20 value 86.565034
iter 30 value 83.801752
iter 40 value 81.388043
iter 50 value 80.068202
iter 60 value 79.453760
iter 70 value 79.356407
iter 80 value 79.220915
iter 90 value 78.929995
iter 100 value 78.717641
final value 78.717641
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.307358
iter 10 value 97.053794
iter 20 value 86.594615
iter 30 value 83.462936
iter 40 value 83.296480
iter 50 value 82.319952
iter 60 value 80.548441
iter 70 value 80.113558
iter 80 value 79.954172
iter 90 value 79.346950
iter 100 value 78.839114
final value 78.839114
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.153408
iter 10 value 94.776693
iter 20 value 90.626719
iter 30 value 83.921631
iter 40 value 80.506810
iter 50 value 79.827703
iter 60 value 79.660077
iter 70 value 79.517946
iter 80 value 79.373246
iter 90 value 79.320621
iter 100 value 79.310415
final value 79.310415
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.345065
iter 10 value 94.886737
iter 20 value 94.783537
iter 30 value 94.067230
iter 40 value 91.361565
iter 50 value 84.648211
iter 60 value 84.070340
iter 70 value 83.690366
iter 80 value 83.442187
iter 90 value 82.797746
iter 100 value 81.270791
final value 81.270791
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.509239
final value 94.485802
converged
Fitting Repeat 2
# weights: 103
initial value 95.113268
final value 94.485822
converged
Fitting Repeat 3
# weights: 103
initial value 109.931417
final value 94.485750
converged
Fitting Repeat 4
# weights: 103
initial value 99.539926
final value 94.485908
converged
Fitting Repeat 5
# weights: 103
initial value 99.207261
iter 10 value 94.485745
iter 20 value 94.484227
iter 30 value 86.619359
iter 40 value 84.443935
iter 50 value 84.442536
iter 60 value 84.196829
final value 84.164547
converged
Fitting Repeat 1
# weights: 305
initial value 104.344929
iter 10 value 94.480667
iter 20 value 94.471788
iter 30 value 94.468447
iter 40 value 94.434860
iter 50 value 93.148062
iter 60 value 82.635502
iter 70 value 82.122673
iter 80 value 82.115421
iter 90 value 82.022871
iter 100 value 82.016107
final value 82.016107
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 96.081376
iter 10 value 94.488894
iter 20 value 94.395945
iter 30 value 93.441819
iter 40 value 87.311699
iter 50 value 85.661430
iter 60 value 84.275252
iter 70 value 84.266909
iter 80 value 84.266266
iter 90 value 84.262971
iter 100 value 84.106428
final value 84.106428
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.088647
iter 10 value 93.957156
iter 20 value 93.951819
iter 30 value 93.675418
iter 40 value 93.282010
iter 50 value 92.614320
final value 92.609266
converged
Fitting Repeat 4
# weights: 305
initial value 101.844593
iter 10 value 94.489429
iter 20 value 94.484066
iter 30 value 89.413119
iter 40 value 85.873676
iter 50 value 85.465962
iter 60 value 84.765865
iter 70 value 78.240768
iter 80 value 76.891211
iter 90 value 76.637524
iter 100 value 76.610410
final value 76.610410
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.238083
iter 10 value 94.054480
iter 20 value 93.702731
iter 30 value 93.698489
iter 40 value 93.695921
iter 50 value 93.692548
iter 60 value 93.469375
iter 70 value 83.486847
iter 80 value 83.348612
iter 90 value 83.338374
iter 100 value 83.338263
final value 83.338263
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 98.995826
iter 10 value 94.491797
iter 20 value 94.068812
iter 30 value 88.214738
iter 40 value 84.941278
iter 50 value 84.523883
iter 60 value 80.638513
iter 70 value 78.323630
iter 80 value 78.297482
iter 90 value 78.288573
iter 100 value 78.251656
final value 78.251656
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 122.984736
iter 10 value 94.932512
iter 20 value 91.349697
iter 30 value 85.568946
iter 40 value 85.386750
iter 50 value 85.382256
iter 60 value 84.966339
iter 70 value 84.962852
iter 80 value 81.408540
iter 90 value 80.790392
iter 100 value 79.990932
final value 79.990932
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 95.740250
iter 10 value 94.469542
iter 20 value 86.462624
iter 30 value 86.081190
iter 40 value 84.395568
iter 50 value 84.392782
iter 60 value 84.391012
iter 70 value 84.349106
iter 80 value 84.345005
iter 90 value 84.344428
iter 100 value 84.342586
final value 84.342586
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 98.212033
iter 10 value 94.297543
iter 20 value 93.710057
iter 30 value 93.705909
iter 40 value 93.699417
iter 50 value 86.579324
iter 60 value 82.938268
iter 70 value 81.728841
iter 80 value 81.493288
iter 90 value 81.489559
iter 100 value 81.489021
final value 81.489021
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 121.195218
iter 10 value 94.147691
iter 20 value 94.143797
iter 30 value 93.702993
iter 40 value 92.763030
iter 50 value 91.275314
iter 60 value 90.791798
iter 70 value 90.718472
iter 80 value 90.718340
final value 90.718328
converged
Fitting Repeat 1
# weights: 103
initial value 101.170221
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 101.885707
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.634500
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 101.242829
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.901992
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 94.295111
iter 10 value 94.032967
iter 10 value 94.032967
iter 10 value 94.032967
final value 94.032967
converged
Fitting Repeat 2
# weights: 305
initial value 100.658094
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 95.115421
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 95.281140
final value 94.052911
converged
Fitting Repeat 5
# weights: 305
initial value 95.391558
final value 93.324529
converged
Fitting Repeat 1
# weights: 507
initial value 96.603560
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 100.900357
final value 94.032967
converged
Fitting Repeat 3
# weights: 507
initial value 127.415358
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 99.383034
iter 10 value 94.034739
final value 94.032967
converged
Fitting Repeat 5
# weights: 507
initial value 120.003643
final value 94.032967
converged
Fitting Repeat 1
# weights: 103
initial value 98.035716
iter 10 value 94.015899
iter 20 value 84.446846
iter 30 value 83.094476
iter 40 value 81.493128
iter 50 value 81.165463
iter 60 value 81.086396
iter 70 value 81.081218
final value 81.081217
converged
Fitting Repeat 2
# weights: 103
initial value 105.906890
iter 10 value 94.054977
iter 20 value 93.887952
iter 30 value 84.541034
iter 40 value 81.556867
iter 50 value 81.182860
iter 60 value 81.137514
iter 70 value 81.088746
final value 81.081216
converged
Fitting Repeat 3
# weights: 103
initial value 109.539376
iter 10 value 93.745669
iter 20 value 83.434133
iter 30 value 82.874939
iter 40 value 82.663925
iter 50 value 81.375615
iter 60 value 81.085597
iter 70 value 81.081220
final value 81.081217
converged
Fitting Repeat 4
# weights: 103
initial value 105.287238
iter 10 value 93.920476
iter 20 value 92.371158
iter 30 value 92.125395
iter 40 value 87.761951
iter 50 value 84.231143
iter 60 value 81.724355
iter 70 value 81.319302
iter 80 value 80.829687
iter 90 value 80.219205
iter 100 value 80.164868
final value 80.164868
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.520223
iter 10 value 93.851065
iter 20 value 83.215138
iter 30 value 81.911334
iter 40 value 81.689931
iter 50 value 80.763671
iter 60 value 80.486696
iter 70 value 80.218889
iter 80 value 80.159385
iter 80 value 80.159385
iter 80 value 80.159385
final value 80.159385
converged
Fitting Repeat 1
# weights: 305
initial value 109.041033
iter 10 value 94.115828
iter 20 value 83.138712
iter 30 value 82.576705
iter 40 value 82.361971
iter 50 value 81.934107
iter 60 value 80.711462
iter 70 value 78.403341
iter 80 value 77.942449
iter 90 value 77.768909
iter 100 value 77.607918
final value 77.607918
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.829190
iter 10 value 94.048285
iter 20 value 87.833079
iter 30 value 82.858204
iter 40 value 81.900013
iter 50 value 81.323556
iter 60 value 80.713348
iter 70 value 80.329880
iter 80 value 78.653337
iter 90 value 78.083607
iter 100 value 77.910275
final value 77.910275
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 108.064681
iter 10 value 94.159978
iter 20 value 93.790885
iter 30 value 90.490177
iter 40 value 89.799161
iter 50 value 89.155632
iter 60 value 88.921995
iter 70 value 85.472787
iter 80 value 84.526709
iter 90 value 82.071409
iter 100 value 79.848831
final value 79.848831
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.632981
iter 10 value 94.689939
iter 20 value 93.160605
iter 30 value 86.495566
iter 40 value 85.405562
iter 50 value 82.715470
iter 60 value 79.416071
iter 70 value 78.577068
iter 80 value 78.484638
iter 90 value 78.313972
iter 100 value 78.281503
final value 78.281503
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 126.290940
iter 10 value 93.996038
iter 20 value 88.741715
iter 30 value 83.183165
iter 40 value 82.494210
iter 50 value 82.332195
iter 60 value 81.207236
iter 70 value 80.300897
iter 80 value 80.256372
iter 90 value 80.211520
iter 100 value 80.106396
final value 80.106396
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.084173
iter 10 value 96.734390
iter 20 value 89.514294
iter 30 value 86.357903
iter 40 value 85.028262
iter 50 value 82.188469
iter 60 value 81.845238
iter 70 value 80.785457
iter 80 value 80.055254
iter 90 value 79.950799
iter 100 value 79.085224
final value 79.085224
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 116.739822
iter 10 value 94.039308
iter 20 value 89.702689
iter 30 value 85.421468
iter 40 value 83.840265
iter 50 value 80.948080
iter 60 value 79.958790
iter 70 value 79.436323
iter 80 value 79.188977
iter 90 value 79.039138
iter 100 value 78.973311
final value 78.973311
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 123.765527
iter 10 value 94.171692
iter 20 value 91.952738
iter 30 value 89.998135
iter 40 value 89.158663
iter 50 value 87.456964
iter 60 value 83.057896
iter 70 value 81.184062
iter 80 value 79.328706
iter 90 value 78.681447
iter 100 value 78.386917
final value 78.386917
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.232113
iter 10 value 93.659010
iter 20 value 91.815808
iter 30 value 90.486416
iter 40 value 86.730693
iter 50 value 80.954432
iter 60 value 79.495881
iter 70 value 79.203287
iter 80 value 78.756640
iter 90 value 78.561874
iter 100 value 78.463902
final value 78.463902
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 116.512057
iter 10 value 93.757582
iter 20 value 89.639895
iter 30 value 83.553088
iter 40 value 80.599477
iter 50 value 79.436384
iter 60 value 78.991401
iter 70 value 78.447263
iter 80 value 78.169699
iter 90 value 77.856227
iter 100 value 77.737488
final value 77.737488
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.409591
iter 10 value 81.153562
iter 20 value 81.143101
iter 30 value 81.022284
iter 40 value 80.845248
final value 80.845245
converged
Fitting Repeat 2
# weights: 103
initial value 107.804757
final value 94.054611
converged
Fitting Repeat 3
# weights: 103
initial value 94.406908
final value 94.034649
converged
Fitting Repeat 4
# weights: 103
initial value 96.536384
final value 94.054445
converged
Fitting Repeat 5
# weights: 103
initial value 99.413954
final value 94.054534
converged
Fitting Repeat 1
# weights: 305
initial value 105.448087
iter 10 value 94.038159
iter 20 value 93.905112
iter 30 value 89.594239
iter 40 value 88.454256
iter 50 value 84.626900
iter 60 value 84.520895
iter 70 value 81.293251
iter 80 value 81.003585
iter 90 value 80.881708
final value 80.860643
converged
Fitting Repeat 2
# weights: 305
initial value 98.063882
iter 10 value 90.039184
iter 20 value 89.550111
iter 30 value 89.449738
iter 40 value 89.388975
iter 50 value 89.362173
iter 60 value 78.786009
iter 70 value 78.145027
iter 80 value 78.035542
iter 90 value 77.694810
iter 100 value 77.536987
final value 77.536987
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 94.489002
iter 10 value 91.932239
iter 20 value 91.376494
iter 30 value 91.375857
iter 40 value 91.371569
iter 50 value 91.371237
iter 60 value 91.187541
iter 70 value 89.200928
iter 80 value 83.027308
iter 90 value 80.295290
iter 100 value 78.606908
final value 78.606908
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 95.295090
iter 10 value 93.329711
iter 20 value 89.806792
iter 30 value 87.861942
iter 40 value 87.250995
iter 50 value 87.211824
final value 87.211689
converged
Fitting Repeat 5
# weights: 305
initial value 118.711487
iter 10 value 87.572140
iter 20 value 80.445505
iter 30 value 79.908294
iter 40 value 79.837441
iter 50 value 79.509996
final value 79.462546
converged
Fitting Repeat 1
# weights: 507
initial value 111.628654
final value 94.040343
converged
Fitting Repeat 2
# weights: 507
initial value 108.922577
iter 10 value 94.041650
iter 20 value 94.021433
iter 30 value 90.991222
iter 40 value 90.827097
iter 50 value 84.728562
iter 60 value 83.871954
iter 70 value 83.870151
iter 80 value 83.862258
iter 90 value 81.544227
iter 100 value 81.494008
final value 81.494008
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 100.617978
iter 10 value 91.528923
iter 20 value 84.739331
iter 30 value 83.292492
iter 40 value 83.010354
iter 50 value 83.003292
iter 60 value 83.002363
iter 70 value 81.226282
iter 80 value 80.809021
iter 90 value 80.805619
final value 80.805103
converged
Fitting Repeat 4
# weights: 507
initial value 109.599417
iter 10 value 94.101292
iter 20 value 89.667890
iter 30 value 81.213983
iter 40 value 81.143699
iter 50 value 81.135395
iter 60 value 80.855175
iter 70 value 80.847322
iter 80 value 80.843953
iter 90 value 80.748756
iter 100 value 80.547497
final value 80.547497
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 102.186124
iter 10 value 94.049457
iter 20 value 94.039293
final value 94.037792
converged
Fitting Repeat 1
# weights: 103
initial value 99.001863
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 105.088111
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.731603
iter 10 value 94.473697
final value 94.026542
converged
Fitting Repeat 4
# weights: 103
initial value 96.504935
final value 94.354286
converged
Fitting Repeat 5
# weights: 103
initial value 100.840302
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 102.175620
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 117.313560
iter 10 value 94.415779
iter 20 value 94.354286
iter 20 value 94.354286
iter 20 value 94.354286
final value 94.354286
converged
Fitting Repeat 3
# weights: 305
initial value 95.814180
iter 10 value 93.225667
iter 20 value 93.221414
final value 93.221353
converged
Fitting Repeat 4
# weights: 305
initial value 100.907852
final value 94.026542
converged
Fitting Repeat 5
# weights: 305
initial value 94.772337
final value 92.376405
converged
Fitting Repeat 1
# weights: 507
initial value 126.581519
iter 10 value 93.951740
final value 93.866667
converged
Fitting Repeat 2
# weights: 507
initial value 128.156617
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 100.269952
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 116.307130
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 112.989686
final value 94.026542
converged
Fitting Repeat 1
# weights: 103
initial value 97.045875
iter 10 value 94.486434
iter 20 value 93.963590
iter 30 value 93.857877
iter 40 value 93.838712
iter 50 value 91.206584
iter 60 value 85.926624
iter 70 value 84.093532
iter 80 value 82.728739
iter 90 value 82.477133
iter 100 value 82.197135
final value 82.197135
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 103.343338
iter 10 value 94.491309
iter 20 value 94.478772
iter 30 value 94.070320
iter 40 value 93.947886
iter 50 value 93.871096
iter 60 value 93.851842
iter 70 value 93.849719
iter 80 value 93.848157
iter 90 value 93.842459
iter 100 value 92.453828
final value 92.453828
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 105.583005
iter 10 value 94.484298
iter 20 value 94.340169
iter 30 value 94.228191
iter 40 value 92.415612
iter 50 value 88.710483
iter 60 value 87.789732
iter 70 value 85.954854
iter 80 value 85.609302
iter 90 value 85.506269
final value 85.505314
converged
Fitting Repeat 4
# weights: 103
initial value 96.852743
iter 10 value 94.486453
iter 20 value 93.992091
iter 30 value 93.843971
iter 40 value 91.878565
iter 50 value 89.342079
iter 60 value 88.298323
iter 70 value 87.613119
iter 80 value 83.085978
iter 90 value 82.561477
iter 100 value 82.301937
final value 82.301937
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 101.994807
iter 10 value 94.513189
iter 20 value 94.470917
iter 30 value 87.143081
iter 40 value 86.826688
iter 50 value 86.812703
iter 60 value 86.234451
iter 70 value 85.943662
final value 85.941498
converged
Fitting Repeat 1
# weights: 305
initial value 108.740278
iter 10 value 94.028857
iter 20 value 83.719033
iter 30 value 82.744977
iter 40 value 82.523718
iter 50 value 82.104054
iter 60 value 81.529215
iter 70 value 81.298304
iter 80 value 81.078029
iter 90 value 81.005931
iter 100 value 80.871029
final value 80.871029
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 119.704391
iter 10 value 95.537683
iter 20 value 94.132540
iter 30 value 93.823900
iter 40 value 88.873324
iter 50 value 88.742362
iter 60 value 86.844168
iter 70 value 85.625338
iter 80 value 84.216543
iter 90 value 83.366217
iter 100 value 82.698742
final value 82.698742
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.788617
iter 10 value 94.495651
iter 20 value 94.477777
iter 30 value 93.456176
iter 40 value 91.181427
iter 50 value 85.585917
iter 60 value 83.958822
iter 70 value 82.384834
iter 80 value 82.045464
iter 90 value 81.604273
iter 100 value 81.318415
final value 81.318415
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.822921
iter 10 value 94.433631
iter 20 value 93.987671
iter 30 value 91.823302
iter 40 value 88.419473
iter 50 value 88.292768
iter 60 value 87.684151
iter 70 value 87.142777
iter 80 value 84.454759
iter 90 value 83.506335
iter 100 value 81.635781
final value 81.635781
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 113.074969
iter 10 value 94.713505
iter 20 value 89.592650
iter 30 value 88.133953
iter 40 value 87.874910
iter 50 value 87.724965
iter 60 value 85.589914
iter 70 value 85.350795
iter 80 value 84.917035
iter 90 value 83.721603
iter 100 value 81.959941
final value 81.959941
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 140.037709
iter 10 value 94.711711
iter 20 value 93.876069
iter 30 value 88.259700
iter 40 value 86.855043
iter 50 value 85.814514
iter 60 value 84.476472
iter 70 value 83.963473
iter 80 value 83.559761
iter 90 value 82.153356
iter 100 value 81.765779
final value 81.765779
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 114.388641
iter 10 value 94.311991
iter 20 value 90.179596
iter 30 value 85.038679
iter 40 value 84.172901
iter 50 value 82.593642
iter 60 value 81.590060
iter 70 value 81.350036
iter 80 value 81.094641
iter 90 value 80.984867
iter 100 value 80.963816
final value 80.963816
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 107.474718
iter 10 value 94.346662
iter 20 value 88.822672
iter 30 value 85.780495
iter 40 value 85.247733
iter 50 value 83.049135
iter 60 value 81.734419
iter 70 value 81.393639
iter 80 value 81.196504
iter 90 value 81.127525
iter 100 value 80.993917
final value 80.993917
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 123.638111
iter 10 value 93.859495
iter 20 value 92.162887
iter 30 value 82.972593
iter 40 value 82.356696
iter 50 value 81.912445
iter 60 value 81.262721
iter 70 value 80.827140
iter 80 value 80.770492
iter 90 value 80.717057
iter 100 value 80.688521
final value 80.688521
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.056517
iter 10 value 93.964831
iter 20 value 86.834173
iter 30 value 85.946874
iter 40 value 83.838004
iter 50 value 81.927793
iter 60 value 81.586098
iter 70 value 81.503332
iter 80 value 81.437165
iter 90 value 81.153146
iter 100 value 81.092045
final value 81.092045
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.529467
iter 10 value 94.485960
iter 20 value 94.479759
iter 30 value 93.763563
final value 93.742199
converged
Fitting Repeat 2
# weights: 103
initial value 100.321552
iter 10 value 94.398919
iter 20 value 94.382953
iter 30 value 94.381975
iter 40 value 93.982421
iter 50 value 93.912933
final value 93.912925
converged
Fitting Repeat 3
# weights: 103
initial value 96.605898
final value 94.485735
converged
Fitting Repeat 4
# weights: 103
initial value 99.914677
final value 94.485742
converged
Fitting Repeat 5
# weights: 103
initial value 103.699703
final value 94.485881
converged
Fitting Repeat 1
# weights: 305
initial value 98.087182
iter 10 value 93.927640
iter 20 value 93.772473
iter 30 value 93.671099
iter 40 value 87.963765
iter 50 value 82.325748
iter 60 value 82.321262
iter 70 value 82.151132
iter 80 value 82.135387
iter 90 value 82.039603
iter 100 value 82.030869
final value 82.030869
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.228452
iter 10 value 94.466216
iter 20 value 92.988079
iter 30 value 86.273768
iter 40 value 86.231517
iter 50 value 86.231246
final value 86.231229
converged
Fitting Repeat 3
# weights: 305
initial value 104.868699
iter 10 value 94.493701
iter 20 value 94.368795
iter 30 value 94.031648
iter 40 value 94.029332
iter 50 value 94.027423
final value 94.026676
converged
Fitting Repeat 4
# weights: 305
initial value 114.669606
iter 10 value 94.485340
final value 94.484239
converged
Fitting Repeat 5
# weights: 305
initial value 96.244253
iter 10 value 94.359368
iter 20 value 94.341251
iter 30 value 92.032240
iter 40 value 92.031069
iter 40 value 92.031068
iter 40 value 92.031068
final value 92.031068
converged
Fitting Repeat 1
# weights: 507
initial value 130.811604
iter 10 value 94.491455
iter 20 value 94.420371
iter 30 value 85.157808
iter 40 value 84.392486
iter 50 value 82.421291
iter 60 value 81.427955
iter 70 value 80.984057
iter 80 value 80.883669
iter 90 value 79.965233
iter 100 value 79.300893
final value 79.300893
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.477253
iter 10 value 94.492034
iter 20 value 94.484633
iter 30 value 87.910315
iter 40 value 86.307510
iter 50 value 84.934501
iter 60 value 84.801415
final value 84.800730
converged
Fitting Repeat 3
# weights: 507
initial value 98.329192
iter 10 value 94.023043
iter 20 value 93.980593
iter 30 value 93.873432
iter 40 value 93.867497
iter 50 value 88.416255
iter 60 value 84.227826
iter 70 value 83.649972
iter 80 value 83.582478
iter 90 value 83.580539
iter 100 value 81.251345
final value 81.251345
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 97.759857
iter 10 value 86.404572
iter 20 value 85.987680
iter 30 value 85.984806
iter 40 value 85.981604
final value 85.981464
converged
Fitting Repeat 5
# weights: 507
initial value 94.501491
iter 10 value 94.034897
iter 20 value 94.026814
iter 30 value 88.083809
iter 40 value 87.813959
iter 50 value 87.457852
iter 60 value 83.477040
iter 70 value 81.442543
iter 80 value 81.361503
iter 90 value 81.327355
iter 100 value 81.326391
final value 81.326391
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 129.451955
iter 10 value 114.749724
iter 20 value 109.431476
iter 30 value 109.116355
iter 40 value 107.969375
iter 50 value 103.586951
iter 60 value 103.120222
iter 70 value 102.829263
iter 80 value 102.626046
iter 90 value 102.379471
iter 100 value 102.056672
final value 102.056672
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 131.708823
iter 10 value 114.087994
iter 20 value 107.365952
iter 30 value 107.179205
iter 40 value 104.037185
iter 50 value 102.739228
iter 60 value 102.077223
iter 70 value 101.718338
iter 80 value 101.652923
iter 90 value 101.193457
iter 100 value 101.086033
final value 101.086033
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 129.752972
iter 10 value 117.068634
iter 20 value 108.543708
iter 30 value 108.137384
iter 40 value 107.888762
iter 50 value 106.782883
iter 60 value 104.357626
iter 70 value 102.459670
iter 80 value 101.911918
iter 90 value 101.073426
iter 100 value 100.655676
final value 100.655676
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 132.580597
iter 10 value 118.017322
iter 20 value 108.478162
iter 30 value 107.332826
iter 40 value 107.007741
iter 50 value 105.692977
iter 60 value 104.025496
iter 70 value 101.831824
iter 80 value 101.358851
iter 90 value 101.175171
iter 100 value 101.045998
final value 101.045998
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 130.850400
iter 10 value 117.924087
iter 20 value 110.098816
iter 30 value 107.359895
iter 40 value 107.230861
iter 50 value 105.603981
iter 60 value 104.877645
iter 70 value 104.756494
iter 80 value 104.749523
iter 90 value 104.715913
iter 100 value 103.128175
final value 103.128175
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 -- Sat Dec 20 00:12:40 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
40.766 1.162 92.700
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.150 | 0.637 | 33.811 | |
| FreqInteractors | 0.442 | 0.027 | 0.469 | |
| calculateAAC | 0.034 | 0.000 | 0.033 | |
| calculateAutocor | 0.311 | 0.017 | 0.328 | |
| calculateCTDC | 0.071 | 0.001 | 0.073 | |
| calculateCTDD | 0.463 | 0.000 | 0.463 | |
| calculateCTDT | 0.133 | 0.002 | 0.135 | |
| calculateCTriad | 0.392 | 0.007 | 0.398 | |
| calculateDC | 0.092 | 0.006 | 0.098 | |
| calculateF | 0.301 | 0.000 | 0.302 | |
| calculateKSAAP | 0.098 | 0.008 | 0.106 | |
| calculateQD_Sm | 1.600 | 0.032 | 1.633 | |
| calculateTC | 1.466 | 0.141 | 1.606 | |
| calculateTC_Sm | 0.268 | 0.004 | 0.272 | |
| corr_plot | 34.175 | 0.381 | 34.591 | |
| enrichfindP | 0.542 | 0.036 | 14.688 | |
| enrichfind_hp | 0.059 | 0.000 | 1.158 | |
| enrichplot | 0.542 | 0.003 | 0.545 | |
| filter_missing_values | 0.002 | 0.000 | 0.002 | |
| getFASTA | 0.410 | 0.008 | 6.469 | |
| getHPI | 0.000 | 0.000 | 0.001 | |
| get_negativePPI | 0.002 | 0.001 | 0.002 | |
| get_positivePPI | 0.001 | 0.000 | 0.000 | |
| impute_missing_data | 0.001 | 0.000 | 0.002 | |
| plotPPI | 0.087 | 0.001 | 0.087 | |
| pred_ensembel | 12.930 | 0.107 | 11.662 | |
| var_imp | 33.463 | 0.382 | 33.904 | |