Matineh Rahmatbakhsh
| Snapshot Date: 2026-05-22 13:40 -0400 (Fri, 22 May 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_23 |
| git_last_commit: 31a0ff7 |
| git_last_commit_date: 2026-04-28 08:56:55 -0400 (Tue, 28 Apr 2026) |
| Back to Build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-05-23 11:32 -0400 (Sat, 23 May 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4995 |
| 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 1030/2418 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.18.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| See other builds for HPiP in R Universe. | ||||||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.18.0 |
| 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_1.18.0.tar.gz |
| StartedAt: 2026-05-23 01:02:43 -0400 (Sat, 23 May 2026) |
| EndedAt: 2026-05-23 01:18:27 -0400 (Sat, 23 May 2026) |
| EllapsedTime: 944.4 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.18.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-05-23 05:02:43 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.18.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
FSmethod 37.737 0.552 38.374
corr_plot 34.449 0.534 35.024
var_imp 33.451 0.556 34.010
pred_ensembel 12.896 0.244 11.953
enrichfindP 0.532 0.041 19.005
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘runTests.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.18.0’ ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 100.347139
iter 10 value 93.025763
iter 20 value 93.017886
iter 20 value 93.017886
iter 20 value 93.017886
final value 93.017886
converged
Fitting Repeat 2
# weights: 103
initial value 103.706966
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.732917
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 100.217661
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 97.667635
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 96.501685
iter 10 value 93.039273
iter 20 value 93.013491
iter 20 value 93.013491
iter 20 value 93.013491
final value 93.013491
converged
Fitting Repeat 2
# weights: 305
initial value 105.772264
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 106.897043
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 108.011479
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 99.268529
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 101.527003
final value 94.026542
converged
Fitting Repeat 2
# weights: 507
initial value 110.617155
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 100.293636
iter 10 value 85.215719
final value 84.822503
converged
Fitting Repeat 4
# weights: 507
initial value 97.943037
final value 93.809648
converged
Fitting Repeat 5
# weights: 507
initial value 96.868879
iter 10 value 88.014695
iter 20 value 86.397657
iter 30 value 85.475175
final value 85.433687
converged
Fitting Repeat 1
# weights: 103
initial value 109.802179
iter 10 value 94.106145
iter 20 value 93.170272
iter 30 value 92.443185
iter 40 value 83.023730
iter 50 value 82.628385
iter 60 value 82.112910
iter 70 value 81.058216
iter 80 value 79.723519
iter 90 value 79.486133
iter 100 value 79.479601
final value 79.479601
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 102.754635
iter 10 value 94.471092
iter 20 value 93.267289
iter 30 value 93.139301
iter 40 value 93.135982
iter 50 value 93.134556
iter 60 value 87.989745
iter 70 value 87.166343
iter 80 value 86.602006
iter 90 value 84.657457
iter 100 value 84.199752
final value 84.199752
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 104.481662
iter 10 value 94.432477
iter 20 value 91.614633
iter 30 value 84.436858
iter 40 value 83.676830
iter 50 value 82.956979
iter 60 value 81.288548
iter 70 value 81.223700
iter 80 value 81.223459
iter 80 value 81.223459
iter 80 value 81.223459
final value 81.223459
converged
Fitting Repeat 4
# weights: 103
initial value 103.201884
iter 10 value 94.127194
iter 20 value 92.556081
iter 30 value 88.107681
iter 40 value 86.838360
iter 50 value 86.383288
iter 60 value 86.305466
iter 70 value 81.875414
iter 80 value 81.118076
iter 90 value 80.339477
iter 100 value 79.767320
final value 79.767320
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 109.289055
iter 10 value 94.492393
iter 20 value 94.352558
iter 30 value 92.574177
iter 40 value 87.221567
iter 50 value 85.378752
iter 60 value 81.788524
iter 70 value 79.691390
iter 80 value 79.532127
iter 90 value 79.510697
iter 100 value 79.483373
final value 79.483373
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 111.535684
iter 10 value 94.132421
iter 20 value 83.501870
iter 30 value 82.654206
iter 40 value 82.007634
iter 50 value 81.495650
iter 60 value 79.905046
iter 70 value 78.876645
iter 80 value 78.207733
iter 90 value 78.171894
iter 100 value 78.163194
final value 78.163194
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.580265
iter 10 value 94.494937
iter 20 value 89.645353
iter 30 value 85.178173
iter 40 value 84.835527
iter 50 value 83.167178
iter 60 value 81.802557
iter 70 value 81.551018
iter 80 value 81.174836
iter 90 value 80.942405
iter 100 value 80.644932
final value 80.644932
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.331208
iter 10 value 94.623801
iter 20 value 93.146677
iter 30 value 82.137651
iter 40 value 81.217617
iter 50 value 80.905884
iter 60 value 80.376470
iter 70 value 79.925293
iter 80 value 79.091129
iter 90 value 78.552808
iter 100 value 78.315874
final value 78.315874
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.484259
iter 10 value 94.499914
iter 20 value 93.944969
iter 30 value 92.190973
iter 40 value 88.516234
iter 50 value 87.751072
iter 60 value 85.675840
iter 70 value 83.811698
iter 80 value 82.189862
iter 90 value 80.518465
iter 100 value 79.488267
final value 79.488267
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.168242
iter 10 value 93.576262
iter 20 value 86.279274
iter 30 value 81.476889
iter 40 value 81.076990
iter 50 value 80.203284
iter 60 value 79.619509
iter 70 value 78.929694
iter 80 value 78.859917
iter 90 value 78.693150
iter 100 value 78.547183
final value 78.547183
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 111.586545
iter 10 value 91.751026
iter 20 value 83.626495
iter 30 value 82.259862
iter 40 value 81.537526
iter 50 value 80.859889
iter 60 value 80.338466
iter 70 value 80.151813
iter 80 value 79.347760
iter 90 value 78.952426
iter 100 value 78.489187
final value 78.489187
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.330397
iter 10 value 99.874694
iter 20 value 92.255611
iter 30 value 89.881100
iter 40 value 87.243530
iter 50 value 84.543323
iter 60 value 80.872929
iter 70 value 80.325340
iter 80 value 79.437138
iter 90 value 78.904218
iter 100 value 78.653765
final value 78.653765
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.920649
iter 10 value 93.716004
iter 20 value 85.743907
iter 30 value 84.692547
iter 40 value 81.625460
iter 50 value 80.535484
iter 60 value 78.949193
iter 70 value 78.571551
iter 80 value 78.433429
iter 90 value 78.273199
iter 100 value 78.193443
final value 78.193443
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.340058
iter 10 value 98.490282
iter 20 value 85.526351
iter 30 value 83.066635
iter 40 value 80.907823
iter 50 value 80.718315
iter 60 value 80.482494
iter 70 value 80.265612
iter 80 value 79.193504
iter 90 value 78.585003
iter 100 value 78.110020
final value 78.110020
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.595668
iter 10 value 94.622801
iter 20 value 90.007879
iter 30 value 85.526250
iter 40 value 83.990212
iter 50 value 82.229412
iter 60 value 81.050032
iter 70 value 80.402281
iter 80 value 79.716570
iter 90 value 79.059314
iter 100 value 78.905256
final value 78.905256
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.625681
iter 10 value 94.028323
iter 20 value 94.026792
iter 30 value 92.282931
iter 40 value 83.488052
iter 50 value 80.129424
iter 60 value 79.040112
iter 70 value 78.779339
iter 80 value 78.745440
final value 78.744998
converged
Fitting Repeat 2
# weights: 103
initial value 95.420514
iter 10 value 93.812044
iter 20 value 93.030531
iter 30 value 93.029329
final value 93.028749
converged
Fitting Repeat 3
# weights: 103
initial value 97.679130
final value 94.485870
converged
Fitting Repeat 4
# weights: 103
initial value 100.006293
final value 94.486083
converged
Fitting Repeat 5
# weights: 103
initial value 98.406436
final value 94.485569
converged
Fitting Repeat 1
# weights: 305
initial value 98.851942
iter 10 value 94.489029
iter 20 value 88.844082
iter 30 value 82.345300
iter 40 value 82.325763
iter 50 value 82.200201
iter 60 value 80.130665
iter 70 value 79.597647
iter 80 value 79.594291
final value 79.594196
converged
Fitting Repeat 2
# weights: 305
initial value 98.011884
iter 10 value 94.488155
iter 20 value 94.411867
iter 30 value 85.715815
iter 40 value 84.199965
iter 50 value 84.194328
iter 60 value 84.194218
iter 70 value 84.193778
iter 80 value 83.569490
iter 90 value 82.610495
iter 100 value 81.762432
final value 81.762432
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.108831
iter 10 value 94.504902
iter 20 value 94.424965
iter 30 value 93.038086
iter 40 value 93.032906
iter 50 value 92.820199
iter 60 value 91.870996
iter 70 value 91.364848
iter 80 value 91.363078
iter 90 value 91.362968
iter 90 value 91.362967
iter 90 value 91.362967
final value 91.362967
converged
Fitting Repeat 4
# weights: 305
initial value 113.788774
iter 10 value 93.301861
iter 20 value 93.297712
iter 30 value 93.295703
iter 40 value 93.288608
iter 50 value 92.350427
iter 60 value 86.202914
iter 70 value 80.721155
iter 80 value 80.081435
final value 80.081208
converged
Fitting Repeat 5
# weights: 305
initial value 120.282728
iter 10 value 94.488893
iter 20 value 94.484160
iter 30 value 86.059064
iter 40 value 85.873955
iter 50 value 85.862893
iter 60 value 85.860226
iter 70 value 85.581599
iter 80 value 84.956650
iter 90 value 84.845468
iter 100 value 84.826092
final value 84.826092
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 100.041671
iter 10 value 94.490351
iter 20 value 94.027405
final value 94.027369
converged
Fitting Repeat 2
# weights: 507
initial value 102.611863
iter 10 value 94.486957
iter 20 value 93.333042
iter 30 value 87.725268
iter 40 value 81.733312
iter 50 value 81.068384
iter 60 value 80.919581
iter 70 value 77.892245
iter 80 value 77.191329
iter 90 value 77.174022
iter 100 value 77.171308
final value 77.171308
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 117.614918
iter 10 value 94.035101
iter 20 value 94.028053
iter 30 value 93.947980
iter 40 value 92.971297
iter 50 value 92.602732
iter 60 value 85.691092
iter 70 value 80.978459
iter 80 value 79.494056
iter 90 value 78.709159
iter 100 value 78.480221
final value 78.480221
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 99.542583
iter 10 value 93.632987
iter 20 value 93.038401
iter 30 value 93.021742
iter 40 value 93.017909
iter 50 value 93.015539
iter 60 value 92.755036
iter 70 value 92.746405
iter 80 value 92.746343
iter 90 value 92.746221
iter 100 value 92.745999
final value 92.745999
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 102.803014
iter 10 value 94.330509
iter 20 value 93.516433
iter 30 value 93.372165
iter 40 value 93.130293
iter 50 value 90.325750
iter 60 value 83.628533
iter 70 value 78.639893
iter 80 value 78.509397
iter 90 value 78.263391
iter 100 value 77.859549
final value 77.859549
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.495973
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 100.603686
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 97.363495
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 94.343165
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 98.604184
iter 10 value 94.052863
iter 10 value 94.052863
iter 10 value 94.052863
final value 94.052863
converged
Fitting Repeat 1
# weights: 305
initial value 113.099278
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 95.407023
final value 93.836066
converged
Fitting Repeat 3
# weights: 305
initial value 103.119461
final value 93.836066
converged
Fitting Repeat 4
# weights: 305
initial value 112.581027
final value 93.836066
converged
Fitting Repeat 5
# weights: 305
initial value 113.793387
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 94.634365
iter 10 value 94.049843
iter 20 value 94.008573
final value 94.007739
converged
Fitting Repeat 2
# weights: 507
initial value 104.049910
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 98.705005
iter 10 value 85.160728
iter 20 value 82.008229
iter 30 value 81.960038
iter 30 value 81.960037
iter 30 value 81.960037
final value 81.960037
converged
Fitting Repeat 4
# weights: 507
initial value 107.289710
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 119.888607
iter 10 value 91.527500
iter 20 value 88.031313
iter 30 value 87.937553
iter 40 value 87.934305
iter 50 value 83.916330
iter 60 value 83.428272
iter 70 value 83.399522
iter 80 value 83.399178
final value 83.399173
converged
Fitting Repeat 1
# weights: 103
initial value 102.452207
iter 10 value 93.920412
iter 20 value 88.066648
iter 30 value 86.327229
iter 40 value 84.503368
iter 50 value 81.236334
iter 60 value 80.339009
iter 70 value 80.015650
iter 80 value 79.978896
iter 90 value 79.958614
iter 100 value 79.913409
final value 79.913409
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.186567
iter 10 value 90.784591
iter 20 value 83.639167
iter 30 value 83.501312
iter 40 value 82.937592
iter 50 value 82.612226
iter 60 value 82.583481
iter 70 value 82.578685
iter 70 value 82.578685
iter 70 value 82.578685
final value 82.578685
converged
Fitting Repeat 3
# weights: 103
initial value 97.781243
iter 10 value 91.949459
iter 20 value 91.498082
iter 30 value 91.455341
iter 40 value 91.448342
iter 50 value 91.435140
final value 91.435139
converged
Fitting Repeat 4
# weights: 103
initial value 97.663561
iter 10 value 94.047903
iter 20 value 87.809940
iter 30 value 81.082985
iter 40 value 80.927945
iter 50 value 80.215744
iter 60 value 79.988424
iter 70 value 79.964335
iter 80 value 79.961282
final value 79.960225
converged
Fitting Repeat 5
# weights: 103
initial value 101.801603
iter 10 value 94.488384
iter 20 value 90.853416
iter 30 value 82.880969
iter 40 value 81.769429
iter 50 value 80.730279
iter 60 value 80.412633
iter 70 value 80.377018
iter 80 value 80.099565
iter 90 value 79.959900
final value 79.956331
converged
Fitting Repeat 1
# weights: 305
initial value 102.528078
iter 10 value 94.057012
iter 20 value 93.839376
iter 30 value 90.646945
iter 40 value 87.073442
iter 50 value 85.634935
iter 60 value 85.184927
iter 70 value 84.706442
iter 80 value 81.383785
iter 90 value 80.568458
iter 100 value 79.834704
final value 79.834704
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.576452
iter 10 value 92.549157
iter 20 value 84.060118
iter 30 value 82.740676
iter 40 value 82.397296
iter 50 value 81.009107
iter 60 value 80.705662
iter 70 value 80.305108
iter 80 value 80.233735
iter 90 value 80.126321
iter 100 value 80.064455
final value 80.064455
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.043055
iter 10 value 94.167584
iter 20 value 93.853089
iter 30 value 87.684722
iter 40 value 86.543926
iter 50 value 86.120289
iter 60 value 83.455018
iter 70 value 80.540496
iter 80 value 80.431758
iter 90 value 80.261505
iter 100 value 80.078599
final value 80.078599
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.308947
iter 10 value 94.579584
iter 20 value 86.786354
iter 30 value 85.699406
iter 40 value 82.433113
iter 50 value 81.597354
iter 60 value 81.197070
iter 70 value 80.627497
iter 80 value 80.078456
iter 90 value 79.889154
iter 100 value 79.865233
final value 79.865233
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.227237
iter 10 value 93.991608
iter 20 value 83.058091
iter 30 value 80.546472
iter 40 value 80.262588
iter 50 value 80.082028
iter 60 value 79.806392
iter 70 value 79.770483
iter 80 value 79.352627
iter 90 value 78.803389
iter 100 value 78.708059
final value 78.708059
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 119.131222
iter 10 value 92.499124
iter 20 value 83.656392
iter 30 value 82.797472
iter 40 value 81.677250
iter 50 value 80.457620
iter 60 value 79.918831
iter 70 value 78.909743
iter 80 value 78.527560
iter 90 value 78.462769
iter 100 value 78.417039
final value 78.417039
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.851797
iter 10 value 97.236988
iter 20 value 85.776936
iter 30 value 84.716348
iter 40 value 82.286190
iter 50 value 80.072198
iter 60 value 79.706140
iter 70 value 79.539831
iter 80 value 79.367070
iter 90 value 79.208596
iter 100 value 79.043846
final value 79.043846
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.424892
iter 10 value 94.016925
iter 20 value 91.390537
iter 30 value 82.426282
iter 40 value 80.758592
iter 50 value 79.637154
iter 60 value 79.258041
iter 70 value 78.861436
iter 80 value 78.707564
iter 90 value 78.289173
iter 100 value 78.072821
final value 78.072821
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 129.689021
iter 10 value 94.076321
iter 20 value 93.179595
iter 30 value 84.042436
iter 40 value 83.251883
iter 50 value 82.801090
iter 60 value 81.804498
iter 70 value 80.923628
iter 80 value 80.173013
iter 90 value 79.517772
iter 100 value 79.053164
final value 79.053164
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.487379
iter 10 value 94.211360
iter 20 value 87.172144
iter 30 value 82.310769
iter 40 value 81.332915
iter 50 value 80.860244
iter 60 value 80.423862
iter 70 value 79.463868
iter 80 value 78.870211
iter 90 value 78.766166
iter 100 value 78.721470
final value 78.721470
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.838136
final value 94.054696
converged
Fitting Repeat 2
# weights: 103
initial value 97.132128
iter 10 value 94.054668
final value 94.053047
converged
Fitting Repeat 3
# weights: 103
initial value 113.202862
iter 10 value 94.054571
iter 20 value 94.053010
iter 30 value 93.773835
iter 40 value 82.677229
iter 50 value 82.510046
iter 60 value 82.505255
final value 82.505207
converged
Fitting Repeat 4
# weights: 103
initial value 97.984269
final value 93.465855
converged
Fitting Repeat 5
# weights: 103
initial value 101.316443
final value 94.054412
converged
Fitting Repeat 1
# weights: 305
initial value 101.105540
iter 10 value 94.057558
iter 20 value 93.963167
iter 30 value 91.655863
iter 40 value 87.878598
iter 50 value 85.107102
iter 60 value 85.100922
final value 85.087475
converged
Fitting Repeat 2
# weights: 305
initial value 106.217317
iter 10 value 94.057776
iter 20 value 94.043636
iter 30 value 89.959938
iter 40 value 88.230121
iter 50 value 80.839748
iter 60 value 80.464043
final value 80.463749
converged
Fitting Repeat 3
# weights: 305
initial value 101.006333
iter 10 value 94.055287
iter 20 value 93.327884
iter 30 value 85.495339
iter 40 value 80.369285
iter 50 value 80.350146
iter 60 value 79.975799
iter 70 value 79.963547
iter 80 value 79.959562
iter 90 value 79.949942
iter 100 value 79.941277
final value 79.941277
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.777601
iter 10 value 93.840911
iter 20 value 93.836471
iter 30 value 93.785912
iter 30 value 93.785912
iter 30 value 93.785912
final value 93.785912
converged
Fitting Repeat 5
# weights: 305
initial value 98.679276
iter 10 value 94.057692
iter 20 value 94.020984
iter 30 value 93.786488
final value 93.785853
converged
Fitting Repeat 1
# weights: 507
initial value 104.000747
iter 10 value 93.844219
iter 20 value 93.801802
iter 30 value 93.760016
iter 40 value 93.340411
iter 50 value 91.923285
iter 60 value 91.922294
iter 70 value 90.581959
iter 80 value 90.570806
iter 90 value 90.567291
iter 100 value 90.560992
final value 90.560992
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.549959
iter 10 value 93.705841
iter 20 value 93.701323
iter 30 value 80.702244
iter 40 value 80.074045
iter 50 value 79.377198
iter 60 value 78.808043
iter 70 value 78.536653
iter 80 value 78.505654
final value 78.505357
converged
Fitting Repeat 3
# weights: 507
initial value 105.551008
iter 10 value 93.844183
iter 20 value 93.836622
final value 93.836475
converged
Fitting Repeat 4
# weights: 507
initial value 138.542530
iter 10 value 94.061467
iter 20 value 94.008040
iter 30 value 84.063878
iter 40 value 83.402194
iter 50 value 83.396162
iter 60 value 83.099634
iter 70 value 82.761878
iter 80 value 82.757644
iter 90 value 82.588748
iter 100 value 81.689416
final value 81.689416
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 93.707726
iter 10 value 91.665000
iter 20 value 91.663205
iter 30 value 91.541147
iter 40 value 84.278714
iter 50 value 84.102457
iter 60 value 84.029741
iter 70 value 83.901242
final value 83.885711
converged
Fitting Repeat 1
# weights: 103
initial value 96.450215
final value 93.915746
converged
Fitting Repeat 2
# weights: 103
initial value 95.731680
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 108.260235
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.016217
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 103.354962
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 104.993460
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 97.242043
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 100.897457
final value 93.915746
converged
Fitting Repeat 4
# weights: 305
initial value 108.387126
iter 10 value 93.282789
iter 20 value 92.673217
iter 20 value 92.673217
iter 20 value 92.673217
final value 92.673217
converged
Fitting Repeat 5
# weights: 305
initial value 100.782516
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 94.748627
final value 94.052911
converged
Fitting Repeat 2
# weights: 507
initial value 94.682260
final value 93.913919
converged
Fitting Repeat 3
# weights: 507
initial value 112.368324
iter 10 value 93.743864
iter 20 value 92.522080
final value 92.514400
converged
Fitting Repeat 4
# weights: 507
initial value 104.099679
iter 10 value 93.526516
final value 93.516417
converged
Fitting Repeat 5
# weights: 507
initial value 113.005080
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 99.355236
iter 10 value 93.359338
iter 20 value 86.395291
iter 30 value 86.037593
iter 40 value 85.304616
iter 50 value 84.948792
iter 60 value 84.933830
iter 70 value 84.930842
iter 80 value 84.790190
iter 90 value 84.717334
final value 84.716531
converged
Fitting Repeat 2
# weights: 103
initial value 96.923298
iter 10 value 94.055211
iter 20 value 93.957736
iter 30 value 93.104274
iter 40 value 92.226150
iter 50 value 91.559648
iter 60 value 87.189665
iter 70 value 86.488586
iter 80 value 85.925513
iter 90 value 83.857697
iter 100 value 83.353901
final value 83.353901
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 99.230471
iter 10 value 91.253430
iter 20 value 85.446607
iter 30 value 85.125628
iter 40 value 84.344814
iter 50 value 83.061903
iter 60 value 82.867896
iter 70 value 82.642575
final value 82.642143
converged
Fitting Repeat 4
# weights: 103
initial value 108.935471
iter 10 value 94.288425
iter 20 value 94.056445
iter 30 value 92.126317
iter 40 value 90.763977
iter 50 value 90.116863
iter 60 value 86.535343
iter 70 value 85.387293
iter 80 value 84.750059
iter 90 value 84.745269
iter 90 value 84.745269
iter 90 value 84.745269
final value 84.745269
converged
Fitting Repeat 5
# weights: 103
initial value 97.313602
iter 10 value 94.006400
iter 20 value 93.087080
iter 30 value 91.674322
iter 40 value 85.463351
iter 50 value 84.888095
iter 60 value 84.783275
final value 84.783266
converged
Fitting Repeat 1
# weights: 305
initial value 107.379398
iter 10 value 89.358794
iter 20 value 85.111036
iter 30 value 84.881330
iter 40 value 84.843214
iter 50 value 84.570379
iter 60 value 83.470448
iter 70 value 83.028183
iter 80 value 82.842368
iter 90 value 82.647327
iter 100 value 82.204793
final value 82.204793
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.923217
iter 10 value 94.019872
iter 20 value 93.045105
iter 30 value 88.910242
iter 40 value 87.273672
iter 50 value 84.565215
iter 60 value 83.498885
iter 70 value 83.116257
iter 80 value 82.351794
iter 90 value 82.229732
iter 100 value 81.943926
final value 81.943926
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.409012
iter 10 value 93.854809
iter 20 value 93.691649
iter 30 value 92.527956
iter 40 value 87.449192
iter 50 value 86.298948
iter 60 value 85.769637
iter 70 value 85.572161
iter 80 value 85.189389
iter 90 value 85.077773
iter 100 value 84.588661
final value 84.588661
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.497039
iter 10 value 94.174078
iter 20 value 93.786115
iter 30 value 92.749081
iter 40 value 91.646125
iter 50 value 91.296724
iter 60 value 86.650787
iter 70 value 85.214054
iter 80 value 84.650257
iter 90 value 83.085592
iter 100 value 81.902218
final value 81.902218
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.747286
iter 10 value 94.071523
iter 20 value 93.953499
iter 30 value 93.555011
iter 40 value 93.087094
iter 50 value 89.338758
iter 60 value 87.365100
iter 70 value 85.529490
iter 80 value 85.167376
iter 90 value 85.014397
iter 100 value 84.905236
final value 84.905236
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.680347
iter 10 value 94.886286
iter 20 value 90.529971
iter 30 value 87.237416
iter 40 value 86.479763
iter 50 value 86.012283
iter 60 value 85.338805
iter 70 value 84.782623
iter 80 value 82.767660
iter 90 value 82.066550
iter 100 value 81.923594
final value 81.923594
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 122.828678
iter 10 value 94.031197
iter 20 value 89.859312
iter 30 value 85.022621
iter 40 value 84.073916
iter 50 value 83.119358
iter 60 value 82.103073
iter 70 value 81.564297
iter 80 value 81.309548
iter 90 value 81.180678
iter 100 value 81.120540
final value 81.120540
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 140.155801
iter 10 value 97.331900
iter 20 value 94.122149
iter 30 value 93.988876
iter 40 value 93.414110
iter 50 value 91.185109
iter 60 value 86.405682
iter 70 value 84.850210
iter 80 value 83.209939
iter 90 value 82.340066
iter 100 value 82.153755
final value 82.153755
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.141151
iter 10 value 93.231735
iter 20 value 89.687271
iter 30 value 85.941035
iter 40 value 84.616564
iter 50 value 83.630181
iter 60 value 82.898683
iter 70 value 81.835254
iter 80 value 81.324347
iter 90 value 81.153928
iter 100 value 80.981025
final value 80.981025
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.972485
iter 10 value 94.056508
iter 20 value 87.605578
iter 30 value 86.427156
iter 40 value 84.728460
iter 50 value 83.778870
iter 60 value 83.117319
iter 70 value 82.935912
iter 80 value 82.425362
iter 90 value 81.995550
iter 100 value 81.857591
final value 81.857591
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.011372
final value 94.054240
converged
Fitting Repeat 2
# weights: 103
initial value 98.534177
iter 10 value 94.054410
iter 20 value 94.052234
iter 30 value 86.477359
iter 40 value 84.108487
iter 50 value 84.086544
iter 60 value 84.077330
final value 84.077310
converged
Fitting Repeat 3
# weights: 103
initial value 96.706013
final value 94.054654
converged
Fitting Repeat 4
# weights: 103
initial value 109.516188
final value 94.054676
converged
Fitting Repeat 5
# weights: 103
initial value 98.089922
final value 94.054549
converged
Fitting Repeat 1
# weights: 305
initial value 97.612211
iter 10 value 88.040798
iter 20 value 87.756587
iter 30 value 87.691427
iter 40 value 87.023418
iter 50 value 85.760352
iter 60 value 84.262573
iter 70 value 84.259589
iter 80 value 84.257700
iter 80 value 84.257700
final value 84.257700
converged
Fitting Repeat 2
# weights: 305
initial value 96.980935
iter 10 value 92.769402
iter 20 value 92.765724
iter 30 value 92.760567
iter 30 value 92.760566
iter 30 value 92.760566
final value 92.760566
converged
Fitting Repeat 3
# weights: 305
initial value 101.810228
iter 10 value 94.057468
iter 20 value 93.981549
iter 30 value 93.286119
iter 40 value 92.801382
iter 50 value 92.775469
iter 60 value 85.684741
iter 70 value 84.383866
iter 80 value 84.167549
iter 90 value 82.666652
iter 100 value 82.622495
final value 82.622495
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 96.811713
iter 10 value 94.057377
iter 20 value 86.519413
iter 30 value 86.171338
iter 40 value 85.712913
iter 50 value 85.200818
iter 60 value 85.196034
iter 70 value 85.194157
iter 80 value 85.003399
iter 90 value 82.236598
iter 100 value 81.001041
final value 81.001041
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.525819
iter 10 value 94.057488
iter 20 value 93.912689
iter 30 value 87.784757
iter 40 value 85.063507
iter 50 value 84.425475
final value 84.420107
converged
Fitting Repeat 1
# weights: 507
initial value 104.423530
iter 10 value 93.923903
iter 20 value 93.894512
iter 30 value 88.662937
iter 40 value 85.079679
iter 50 value 85.069605
iter 60 value 85.069254
iter 70 value 85.069019
iter 70 value 85.069019
final value 85.069019
converged
Fitting Repeat 2
# weights: 507
initial value 126.712167
iter 10 value 93.924033
iter 20 value 93.922613
iter 30 value 93.917195
iter 40 value 92.913278
iter 50 value 88.570911
iter 60 value 85.748699
iter 70 value 83.760132
iter 80 value 83.672645
iter 90 value 83.671253
iter 100 value 83.498319
final value 83.498319
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 129.701770
iter 10 value 94.061539
iter 20 value 94.032743
iter 30 value 93.718408
iter 40 value 86.792253
iter 50 value 84.517920
iter 60 value 84.229479
final value 84.228697
converged
Fitting Repeat 4
# weights: 507
initial value 98.206071
iter 10 value 94.060508
iter 20 value 93.831709
iter 30 value 91.927499
iter 40 value 88.604233
iter 50 value 88.525503
iter 60 value 88.524713
iter 70 value 88.523277
final value 88.522885
converged
Fitting Repeat 5
# weights: 507
initial value 105.532743
iter 10 value 94.061223
iter 20 value 93.964451
iter 30 value 93.606432
iter 40 value 93.458974
iter 50 value 87.715485
iter 60 value 85.646427
iter 70 value 85.630436
iter 80 value 85.495105
iter 90 value 85.214127
iter 100 value 85.192078
final value 85.192078
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.631165
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.783921
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 99.921357
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.904359
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 109.452954
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 94.580278
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 101.968240
final value 94.291892
converged
Fitting Repeat 3
# weights: 305
initial value 95.704980
iter 10 value 94.179709
final value 94.174194
converged
Fitting Repeat 4
# weights: 305
initial value 99.656503
iter 10 value 94.484329
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 95.812308
final value 94.428840
converged
Fitting Repeat 1
# weights: 507
initial value 124.250228
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 103.104666
final value 94.291892
converged
Fitting Repeat 3
# weights: 507
initial value 95.169664
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 109.211883
final value 94.291892
converged
Fitting Repeat 5
# weights: 507
initial value 131.619462
iter 10 value 94.163330
iter 20 value 93.938490
iter 30 value 93.938384
final value 93.938381
converged
Fitting Repeat 1
# weights: 103
initial value 100.889648
iter 10 value 94.486062
iter 20 value 92.286533
iter 30 value 86.665102
iter 40 value 86.466266
iter 50 value 85.984363
iter 60 value 84.826959
iter 70 value 82.607228
iter 80 value 82.163415
iter 90 value 81.976514
iter 100 value 81.611744
final value 81.611744
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.686972
iter 10 value 94.458795
iter 20 value 93.104584
iter 30 value 88.821245
iter 40 value 87.178333
iter 50 value 86.953689
iter 60 value 85.540541
iter 70 value 84.752839
iter 80 value 83.925152
iter 90 value 83.787687
iter 100 value 83.470970
final value 83.470970
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 113.138107
iter 10 value 92.919128
iter 20 value 87.534837
iter 30 value 87.116330
iter 40 value 85.397802
iter 50 value 84.950446
iter 60 value 83.976184
iter 70 value 83.331757
iter 80 value 83.285696
iter 90 value 83.285155
final value 83.285152
converged
Fitting Repeat 4
# weights: 103
initial value 107.044565
iter 10 value 94.437486
iter 20 value 92.065513
iter 30 value 91.673065
iter 40 value 91.568142
iter 50 value 91.487860
iter 60 value 91.384044
iter 70 value 91.372332
final value 91.372035
converged
Fitting Repeat 5
# weights: 103
initial value 97.642960
iter 10 value 90.288223
iter 20 value 86.005112
iter 30 value 83.502665
iter 40 value 83.067227
iter 50 value 82.816829
iter 60 value 82.813080
final value 82.812893
converged
Fitting Repeat 1
# weights: 305
initial value 101.507628
iter 10 value 94.508097
iter 20 value 93.866456
iter 30 value 93.028259
iter 40 value 91.743992
iter 50 value 89.936101
iter 60 value 89.606567
iter 70 value 88.817611
iter 80 value 85.334309
iter 90 value 83.931264
iter 100 value 81.154233
final value 81.154233
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 105.439355
iter 10 value 94.536404
iter 20 value 90.730740
iter 30 value 85.728278
iter 40 value 84.584292
iter 50 value 81.800587
iter 60 value 80.489419
iter 70 value 80.040620
iter 80 value 79.688008
iter 90 value 79.659484
iter 100 value 79.637745
final value 79.637745
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.686364
iter 10 value 94.623189
iter 20 value 93.966863
iter 30 value 89.236648
iter 40 value 85.059705
iter 50 value 83.224711
iter 60 value 80.737830
iter 70 value 79.902652
iter 80 value 79.721669
iter 90 value 79.541432
iter 100 value 79.515565
final value 79.515565
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.798267
iter 10 value 94.155748
iter 20 value 88.630374
iter 30 value 85.402669
iter 40 value 83.142021
iter 50 value 82.865923
iter 60 value 81.176332
iter 70 value 79.981770
iter 80 value 79.606410
iter 90 value 79.265655
iter 100 value 78.890285
final value 78.890285
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 124.784057
iter 10 value 94.671340
iter 20 value 94.453909
iter 30 value 91.301110
iter 40 value 86.765214
iter 50 value 86.295544
iter 60 value 86.204535
iter 70 value 85.550548
iter 80 value 83.377489
iter 90 value 82.447948
iter 100 value 81.378263
final value 81.378263
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 128.072195
iter 10 value 96.792202
iter 20 value 85.776468
iter 30 value 83.394840
iter 40 value 82.020110
iter 50 value 80.281375
iter 60 value 80.218243
iter 70 value 79.870210
iter 80 value 79.404201
iter 90 value 79.193910
iter 100 value 79.162823
final value 79.162823
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.465888
iter 10 value 95.060174
iter 20 value 90.317201
iter 30 value 86.976853
iter 40 value 84.967111
iter 50 value 84.369925
iter 60 value 83.226767
iter 70 value 83.007358
iter 80 value 82.630990
iter 90 value 82.503410
iter 100 value 82.490761
final value 82.490761
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.677554
iter 10 value 94.307410
iter 20 value 87.074225
iter 30 value 85.167857
iter 40 value 83.993401
iter 50 value 83.780986
iter 60 value 83.542281
iter 70 value 82.582267
iter 80 value 80.966844
iter 90 value 80.027517
iter 100 value 79.317563
final value 79.317563
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 117.042085
iter 10 value 94.698203
iter 20 value 88.157971
iter 30 value 85.404972
iter 40 value 84.405489
iter 50 value 83.051297
iter 60 value 82.783204
iter 70 value 82.489854
iter 80 value 82.055204
iter 90 value 81.344305
iter 100 value 80.696557
final value 80.696557
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.693506
iter 10 value 93.862837
iter 20 value 87.787981
iter 30 value 85.834910
iter 40 value 81.169594
iter 50 value 80.528970
iter 60 value 80.227065
iter 70 value 80.084485
iter 80 value 79.735785
iter 90 value 79.406780
iter 100 value 79.053768
final value 79.053768
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 107.497310
iter 10 value 94.500097
iter 20 value 94.484563
final value 94.484215
converged
Fitting Repeat 2
# weights: 103
initial value 99.576604
final value 94.485813
converged
Fitting Repeat 3
# weights: 103
initial value 92.738874
iter 10 value 88.049841
iter 20 value 87.953908
iter 30 value 87.949722
final value 87.949694
converged
Fitting Repeat 4
# weights: 103
initial value 97.743824
final value 94.485945
converged
Fitting Repeat 5
# weights: 103
initial value 95.928367
final value 94.485956
converged
Fitting Repeat 1
# weights: 305
initial value 109.841997
iter 10 value 94.488675
iter 20 value 94.322649
final value 94.293569
converged
Fitting Repeat 2
# weights: 305
initial value 101.408478
iter 10 value 94.488672
iter 20 value 94.445430
iter 30 value 92.308967
iter 40 value 85.435239
iter 50 value 84.972366
iter 60 value 84.950419
final value 84.950066
converged
Fitting Repeat 3
# weights: 305
initial value 96.841792
iter 10 value 94.296706
iter 20 value 91.558935
iter 30 value 86.496871
final value 86.496867
converged
Fitting Repeat 4
# weights: 305
initial value 113.100780
iter 10 value 94.296997
iter 20 value 94.292655
iter 30 value 93.560709
iter 40 value 85.528538
iter 50 value 85.520293
iter 60 value 84.523674
iter 70 value 84.112152
iter 80 value 84.089540
iter 90 value 84.065560
iter 100 value 83.638272
final value 83.638272
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.377315
iter 10 value 94.330956
iter 20 value 94.275315
iter 30 value 94.267884
iter 40 value 87.537517
iter 50 value 86.389142
final value 86.385700
converged
Fitting Repeat 1
# weights: 507
initial value 100.603590
iter 10 value 93.476499
iter 20 value 92.389134
iter 30 value 92.294550
iter 40 value 92.126269
iter 50 value 92.124601
iter 60 value 91.406734
iter 70 value 91.406422
iter 80 value 91.105798
iter 90 value 87.016747
iter 100 value 81.276755
final value 81.276755
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.099247
iter 10 value 94.493245
iter 20 value 94.484892
iter 30 value 94.385160
iter 40 value 86.473371
iter 50 value 84.391282
iter 60 value 83.798052
iter 70 value 83.594344
iter 80 value 83.562727
iter 90 value 82.390446
iter 100 value 82.036695
final value 82.036695
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 121.699659
iter 10 value 94.491571
iter 20 value 93.894506
iter 30 value 86.480912
iter 40 value 82.849875
iter 50 value 82.322984
final value 82.314400
converged
Fitting Repeat 4
# weights: 507
initial value 94.867128
iter 10 value 91.963770
iter 20 value 91.004333
iter 30 value 91.003490
iter 40 value 90.909796
iter 50 value 90.904424
iter 60 value 90.904047
iter 70 value 90.902950
iter 80 value 90.526172
final value 90.436567
converged
Fitting Repeat 5
# weights: 507
initial value 107.074976
iter 10 value 94.492401
iter 20 value 91.267663
iter 30 value 88.148015
iter 40 value 82.088341
iter 50 value 81.090953
iter 60 value 80.778945
iter 70 value 80.621353
iter 80 value 80.620419
final value 80.620376
converged
Fitting Repeat 1
# weights: 103
initial value 102.486370
final value 94.325946
converged
Fitting Repeat 2
# weights: 103
initial value 101.117985
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 110.987802
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 109.726434
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 98.481401
iter 10 value 92.243005
iter 20 value 92.063795
iter 30 value 92.025598
final value 92.025557
converged
Fitting Repeat 1
# weights: 305
initial value 98.791597
final value 94.484210
converged
Fitting Repeat 2
# weights: 305
initial value 97.196768
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 104.337204
iter 10 value 94.275363
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 4
# weights: 305
initial value 98.180286
final value 94.484210
converged
Fitting Repeat 5
# weights: 305
initial value 119.671696
final value 94.479532
converged
Fitting Repeat 1
# weights: 507
initial value 106.469790
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 108.440700
iter 10 value 93.178915
iter 20 value 89.305778
iter 30 value 88.368555
iter 40 value 88.309506
final value 88.308708
converged
Fitting Repeat 3
# weights: 507
initial value 99.071435
iter 10 value 91.585978
iter 20 value 90.580838
final value 90.580750
converged
Fitting Repeat 4
# weights: 507
initial value 106.198716
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 106.062270
iter 10 value 94.275363
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 1
# weights: 103
initial value 99.258976
iter 10 value 94.463770
iter 20 value 91.718767
iter 30 value 89.488871
iter 40 value 86.662471
iter 50 value 85.445781
iter 60 value 84.834978
iter 70 value 84.402518
iter 80 value 84.237313
iter 90 value 84.235437
iter 100 value 83.288225
final value 83.288225
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.593878
iter 10 value 93.971678
iter 20 value 88.524248
iter 30 value 86.999095
iter 40 value 86.712465
iter 50 value 86.492576
iter 60 value 86.044622
iter 70 value 85.898339
final value 85.898241
converged
Fitting Repeat 3
# weights: 103
initial value 104.027833
iter 10 value 94.482958
iter 20 value 93.561276
iter 30 value 86.797366
iter 40 value 86.095398
iter 50 value 85.641226
iter 60 value 83.797257
iter 70 value 83.290983
iter 80 value 83.240733
iter 90 value 83.184868
final value 83.168480
converged
Fitting Repeat 4
# weights: 103
initial value 106.797041
iter 10 value 94.491094
iter 20 value 94.008377
iter 30 value 89.117341
iter 40 value 87.119033
iter 50 value 86.576196
iter 60 value 84.226513
iter 70 value 83.873804
iter 80 value 83.260463
iter 90 value 83.227470
iter 100 value 83.168972
final value 83.168972
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 107.216399
iter 10 value 92.005193
iter 20 value 88.212187
iter 30 value 87.746000
iter 40 value 85.803820
iter 50 value 84.777909
iter 60 value 83.673848
iter 70 value 83.150451
iter 80 value 83.099705
iter 90 value 83.076793
iter 100 value 83.055403
final value 83.055403
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 124.023367
iter 10 value 94.679805
iter 20 value 93.458597
iter 30 value 89.716651
iter 40 value 87.131245
iter 50 value 85.740241
iter 60 value 84.671553
iter 70 value 83.497038
iter 80 value 83.245070
iter 90 value 82.699770
iter 100 value 82.396715
final value 82.396715
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.311195
iter 10 value 94.341966
iter 20 value 88.827555
iter 30 value 87.491069
iter 40 value 85.712110
iter 50 value 84.689939
iter 60 value 83.914824
iter 70 value 83.690337
iter 80 value 83.565111
iter 90 value 83.525250
iter 100 value 82.987814
final value 82.987814
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.925277
iter 10 value 94.490864
iter 20 value 93.724495
iter 30 value 90.382090
iter 40 value 86.474861
iter 50 value 84.413994
iter 60 value 83.313192
iter 70 value 82.727111
iter 80 value 82.590654
iter 90 value 82.529450
iter 100 value 82.291965
final value 82.291965
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 121.911159
iter 10 value 93.441584
iter 20 value 92.359200
iter 30 value 91.657949
iter 40 value 85.156478
iter 50 value 84.698971
iter 60 value 84.485630
iter 70 value 83.850007
iter 80 value 83.167626
iter 90 value 82.887959
iter 100 value 82.307633
final value 82.307633
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.886358
iter 10 value 94.425876
iter 20 value 92.636625
iter 30 value 91.809053
iter 40 value 91.187030
iter 50 value 85.688899
iter 60 value 85.253626
iter 70 value 84.748157
iter 80 value 84.531109
iter 90 value 83.758503
iter 100 value 83.259012
final value 83.259012
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 126.564029
iter 10 value 94.673064
iter 20 value 89.140803
iter 30 value 85.540966
iter 40 value 83.724415
iter 50 value 83.076657
iter 60 value 82.188540
iter 70 value 81.830101
iter 80 value 81.811579
iter 90 value 81.775253
iter 100 value 81.709136
final value 81.709136
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.929880
iter 10 value 92.826443
iter 20 value 89.406241
iter 30 value 86.551882
iter 40 value 85.141020
iter 50 value 83.613901
iter 60 value 82.709276
iter 70 value 82.307377
iter 80 value 82.205023
iter 90 value 82.183098
iter 100 value 82.150778
final value 82.150778
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.832189
iter 10 value 94.663401
iter 20 value 92.364135
iter 30 value 90.202825
iter 40 value 86.640727
iter 50 value 86.273658
iter 60 value 86.159764
iter 70 value 85.700485
iter 80 value 83.976757
iter 90 value 83.511875
iter 100 value 83.191631
final value 83.191631
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 114.211540
iter 10 value 95.459045
iter 20 value 89.929980
iter 30 value 87.283028
iter 40 value 86.291688
iter 50 value 84.946906
iter 60 value 82.790295
iter 70 value 82.279369
iter 80 value 82.001795
iter 90 value 81.772662
iter 100 value 81.703276
final value 81.703276
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 123.772421
iter 10 value 94.500866
iter 20 value 88.036026
iter 30 value 86.404675
iter 40 value 86.014775
iter 50 value 85.314507
iter 60 value 84.310105
iter 70 value 84.141374
iter 80 value 83.494710
iter 90 value 82.577594
iter 100 value 82.146135
final value 82.146135
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 101.149440
final value 94.486309
converged
Fitting Repeat 2
# weights: 103
initial value 103.206841
iter 10 value 94.487243
final value 94.485398
converged
Fitting Repeat 3
# weights: 103
initial value 96.599919
final value 94.485721
converged
Fitting Repeat 4
# weights: 103
initial value 107.663675
iter 10 value 94.277287
iter 20 value 94.275937
iter 30 value 93.988889
iter 40 value 91.665750
iter 50 value 85.761399
iter 60 value 84.899069
iter 70 value 84.759004
iter 80 value 84.661433
iter 90 value 84.599671
final value 84.599597
converged
Fitting Repeat 5
# weights: 103
initial value 98.458064
iter 10 value 94.485726
final value 94.484215
converged
Fitting Repeat 1
# weights: 305
initial value 100.219414
iter 10 value 94.097070
iter 20 value 91.446317
iter 30 value 91.418007
iter 40 value 91.410625
iter 50 value 91.295334
iter 60 value 89.240020
iter 70 value 87.015873
iter 80 value 86.950437
iter 90 value 86.950111
iter 100 value 85.948199
final value 85.948199
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 96.719878
iter 10 value 94.320532
iter 20 value 94.279303
iter 30 value 92.401628
iter 40 value 90.943816
iter 50 value 90.652239
iter 60 value 90.649691
final value 90.649673
converged
Fitting Repeat 3
# weights: 305
initial value 95.013357
iter 10 value 94.488662
iter 20 value 94.458467
iter 30 value 93.889854
iter 40 value 93.804798
final value 93.804746
converged
Fitting Repeat 4
# weights: 305
initial value 104.650371
iter 10 value 94.488644
final value 94.484266
converged
Fitting Repeat 5
# weights: 305
initial value 105.529662
iter 10 value 94.488823
final value 94.484217
converged
Fitting Repeat 1
# weights: 507
initial value 106.399991
iter 10 value 94.492367
iter 20 value 94.484595
iter 30 value 94.484111
iter 40 value 86.155016
iter 50 value 85.560885
iter 60 value 83.022698
iter 70 value 82.406396
iter 80 value 82.279746
iter 90 value 82.162391
iter 100 value 82.132335
final value 82.132335
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 97.874419
iter 10 value 93.916902
iter 20 value 93.754136
iter 30 value 93.746854
iter 40 value 93.502583
iter 50 value 89.086875
iter 60 value 88.169552
iter 70 value 88.165665
final value 88.165616
converged
Fitting Repeat 3
# weights: 507
initial value 137.007031
iter 10 value 94.284929
iter 20 value 94.276976
iter 30 value 93.882350
iter 40 value 86.378657
iter 50 value 86.331960
iter 60 value 86.331349
iter 70 value 86.329760
iter 70 value 86.329760
final value 86.329760
converged
Fitting Repeat 4
# weights: 507
initial value 108.355473
iter 10 value 94.492050
iter 20 value 94.484295
iter 30 value 93.494520
iter 40 value 93.447056
iter 50 value 93.410084
iter 60 value 93.405090
final value 93.405041
converged
Fitting Repeat 5
# weights: 507
initial value 103.681962
iter 10 value 94.284233
iter 20 value 94.276320
iter 30 value 93.248021
iter 40 value 92.217836
iter 50 value 91.839446
iter 60 value 91.517958
iter 70 value 91.517262
iter 80 value 91.423269
iter 90 value 89.883460
iter 100 value 88.284530
final value 88.284530
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 125.107227
final value 117.892160
converged
Fitting Repeat 2
# weights: 103
initial value 129.190923
final value 117.891938
converged
Fitting Repeat 3
# weights: 103
initial value 140.495740
final value 117.891905
converged
Fitting Repeat 4
# weights: 103
initial value 119.460738
final value 117.892331
converged
Fitting Repeat 5
# weights: 103
initial value 119.713861
final value 117.891679
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Sat May 23 01:08:35 2026
***********************************************
Number of test functions: 7
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7
Number of errors: 0
Number of failures: 0
Warning messages:
1: `repeats` has no meaning for this resampling method.
2: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
40.109 0.869 115.184
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 37.737 | 0.552 | 38.374 | |
| FreqInteractors | 0.460 | 0.021 | 0.481 | |
| calculateAAC | 0.038 | 0.002 | 0.039 | |
| calculateAutocor | 0.305 | 0.015 | 0.321 | |
| calculateCTDC | 0.094 | 0.002 | 0.096 | |
| calculateCTDD | 0.551 | 0.001 | 0.552 | |
| calculateCTDT | 0.141 | 0.001 | 0.141 | |
| calculateCTriad | 0.431 | 0.030 | 0.461 | |
| calculateDC | 0.087 | 0.022 | 0.108 | |
| calculateF | 0.340 | 0.015 | 0.356 | |
| calculateKSAAP | 0.104 | 0.005 | 0.110 | |
| calculateQD_Sm | 1.799 | 0.103 | 1.902 | |
| calculateTC | 1.581 | 0.207 | 1.788 | |
| calculateTC_Sm | 0.305 | 0.024 | 0.329 | |
| corr_plot | 34.449 | 0.534 | 35.024 | |
| enrichfindP | 0.532 | 0.041 | 19.005 | |
| enrichfind_hp | 0.078 | 0.001 | 1.167 | |
| enrichplot | 0.498 | 0.003 | 0.500 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.408 | 0.009 | 4.104 | |
| getHPI | 0.001 | 0.000 | 0.001 | |
| get_negativePPI | 0.002 | 0.000 | 0.002 | |
| get_positivePPI | 0.001 | 0.000 | 0.000 | |
| impute_missing_data | 0.002 | 0.000 | 0.002 | |
| plotPPI | 0.082 | 0.001 | 0.082 | |
| pred_ensembel | 12.896 | 0.244 | 11.953 | |
| var_imp | 33.451 | 0.556 | 34.010 | |