Matineh Rahmatbakhsh
| Snapshot Date: 2026-02-22 13:45 -0500 (Sun, 22 Feb 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_22 |
| git_last_commit: 6cf0d22 |
| git_last_commit_date: 2025-12-28 18:31:13 -0500 (Sun, 28 Dec 2025) |
| Back to Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-02-23 11:57 -0500 (Mon, 23 Feb 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" | 4890 |
| 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 1006/2361 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.16.1 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.3 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: 1.16.1 |
| Command: /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz |
| StartedAt: 2026-02-23 00:43:11 -0500 (Mon, 23 Feb 2026) |
| EndedAt: 2026-02-23 00:58:10 -0500 (Mon, 23 Feb 2026) |
| EllapsedTime: 899.0 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.22-bioc/R/site-library --timings HPiP_1.16.1.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.22-bioc/meat/HPiP.Rcheck’
* using R version 4.5.2 (2025-10-31)
* 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 ‘1.16.1’
* 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 ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
corr_plot 34.248 0.472 34.776
FSmethod 33.263 0.428 33.775
var_imp 32.984 0.559 33.544
pred_ensembel 12.532 0.096 11.364
enrichfindP 0.491 0.038 12.781
* 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-3.22-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.22-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.22-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.16.1’ ** 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 version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble"
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 96.041847
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.880937
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.094497
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.036422
final value 94.275362
converged
Fitting Repeat 5
# weights: 103
initial value 105.620813
iter 10 value 94.276975
final value 94.275361
converged
Fitting Repeat 1
# weights: 305
initial value 96.956100
final value 94.448052
converged
Fitting Repeat 2
# weights: 305
initial value 99.692818
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 111.486893
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 95.823637
iter 10 value 93.571116
iter 20 value 93.460526
final value 93.460022
converged
Fitting Repeat 5
# weights: 305
initial value 98.669420
final value 94.275362
converged
Fitting Repeat 1
# weights: 507
initial value 98.674614
iter 10 value 92.399620
final value 92.387354
converged
Fitting Repeat 2
# weights: 507
initial value 116.034674
iter 10 value 94.468716
iter 20 value 94.284726
final value 94.275362
converged
Fitting Repeat 3
# weights: 507
initial value 119.318247
final value 94.252920
converged
Fitting Repeat 4
# weights: 507
initial value 111.328276
final value 94.484210
converged
Fitting Repeat 5
# weights: 507
initial value 107.313730
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 109.908579
iter 10 value 94.457021
iter 20 value 91.438214
iter 30 value 89.089843
iter 40 value 85.520225
iter 50 value 84.932163
iter 60 value 84.256278
iter 70 value 83.887438
iter 80 value 81.716604
iter 90 value 80.737299
iter 100 value 80.583680
final value 80.583680
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 103.825042
iter 10 value 94.517376
iter 20 value 94.353483
iter 30 value 90.765203
iter 40 value 90.383065
iter 50 value 89.342347
iter 60 value 86.092039
iter 70 value 85.609358
iter 80 value 85.235533
iter 90 value 85.105618
iter 100 value 84.681720
final value 84.681720
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 99.407892
iter 10 value 94.623328
iter 20 value 94.488677
iter 30 value 94.290510
iter 40 value 87.016380
iter 50 value 86.409780
iter 60 value 86.148068
iter 70 value 85.294110
iter 80 value 84.926393
iter 90 value 84.880686
iter 100 value 84.151978
final value 84.151978
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 107.206071
iter 10 value 94.398727
iter 20 value 94.244623
iter 30 value 85.636164
iter 40 value 84.822717
iter 50 value 84.249686
iter 60 value 84.099681
iter 70 value 82.902391
iter 80 value 82.383660
iter 90 value 82.020313
iter 100 value 81.930388
final value 81.930388
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.812224
iter 10 value 94.483994
iter 20 value 94.384702
iter 30 value 94.259287
iter 40 value 94.249335
iter 50 value 94.187959
iter 60 value 87.957415
iter 70 value 86.617147
iter 80 value 85.243707
iter 90 value 85.166241
iter 100 value 85.099181
final value 85.099181
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 117.315739
iter 10 value 94.395861
iter 20 value 89.978457
iter 30 value 88.740206
iter 40 value 85.650418
iter 50 value 85.039779
iter 60 value 84.818527
iter 70 value 84.726373
iter 80 value 84.568401
iter 90 value 84.463836
iter 100 value 83.587273
final value 83.587273
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.046869
iter 10 value 91.930150
iter 20 value 85.715272
iter 30 value 85.172216
iter 40 value 84.806599
iter 50 value 84.137769
iter 60 value 83.738738
iter 70 value 83.364566
iter 80 value 82.767807
iter 90 value 82.360331
iter 100 value 81.631313
final value 81.631313
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 113.720514
iter 10 value 94.356760
iter 20 value 89.273200
iter 30 value 86.602192
iter 40 value 83.810695
iter 50 value 83.164450
iter 60 value 83.014888
iter 70 value 82.957193
iter 80 value 82.805890
iter 90 value 82.322185
iter 100 value 82.246157
final value 82.246157
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.004920
iter 10 value 94.422382
iter 20 value 91.991123
iter 30 value 83.658101
iter 40 value 81.973884
iter 50 value 80.969691
iter 60 value 79.597465
iter 70 value 79.328577
iter 80 value 79.237558
iter 90 value 79.154236
iter 100 value 79.023446
final value 79.023446
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 110.744581
iter 10 value 91.146648
iter 20 value 86.138479
iter 30 value 84.736365
iter 40 value 81.393270
iter 50 value 79.630693
iter 60 value 79.375368
iter 70 value 79.218852
iter 80 value 79.196889
final value 79.194096
converged
Fitting Repeat 1
# weights: 507
initial value 108.211703
iter 10 value 96.852410
iter 20 value 86.079411
iter 30 value 85.582496
iter 40 value 83.220743
iter 50 value 80.061627
iter 60 value 79.656050
iter 70 value 79.230992
iter 80 value 78.955503
iter 90 value 78.903336
iter 100 value 78.797583
final value 78.797583
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.144197
iter 10 value 94.783554
iter 20 value 87.709692
iter 30 value 85.208333
iter 40 value 84.981666
iter 50 value 84.212208
iter 60 value 81.988999
iter 70 value 81.604812
iter 80 value 80.703777
iter 90 value 80.009976
iter 100 value 79.177820
final value 79.177820
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 120.194566
iter 10 value 99.480939
iter 20 value 94.584953
iter 30 value 87.087735
iter 40 value 84.637019
iter 50 value 82.309677
iter 60 value 80.344445
iter 70 value 79.361946
iter 80 value 78.847140
iter 90 value 78.301979
iter 100 value 78.254994
final value 78.254994
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.491181
iter 10 value 94.425232
iter 20 value 93.508120
iter 30 value 90.392639
iter 40 value 90.065317
iter 50 value 84.333391
iter 60 value 82.289859
iter 70 value 80.425098
iter 80 value 79.534381
iter 90 value 79.163421
iter 100 value 78.705807
final value 78.705807
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 111.580776
iter 10 value 95.456976
iter 20 value 93.443359
iter 30 value 90.045380
iter 40 value 83.335950
iter 50 value 82.333064
iter 60 value 81.853967
iter 70 value 81.555880
iter 80 value 81.528352
iter 90 value 81.487522
iter 100 value 81.300724
final value 81.300724
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.051779
final value 94.485993
converged
Fitting Repeat 2
# weights: 103
initial value 98.438582
final value 94.485916
converged
Fitting Repeat 3
# weights: 103
initial value 95.502937
final value 94.485936
converged
Fitting Repeat 4
# weights: 103
initial value 106.814006
final value 94.486392
converged
Fitting Repeat 5
# weights: 103
initial value 97.245092
iter 10 value 94.276838
iter 20 value 94.275627
final value 94.275478
converged
Fitting Repeat 1
# weights: 305
initial value 101.735535
iter 10 value 88.796094
iter 20 value 87.878454
iter 30 value 87.847341
iter 40 value 87.844505
iter 50 value 87.843303
iter 60 value 87.841902
final value 87.841880
converged
Fitting Repeat 2
# weights: 305
initial value 109.573879
iter 10 value 94.489032
iter 20 value 94.484230
final value 94.484216
converged
Fitting Repeat 3
# weights: 305
initial value 96.626004
iter 10 value 94.488883
iter 20 value 94.455511
iter 30 value 92.937099
iter 30 value 92.937099
iter 30 value 92.937099
final value 92.937099
converged
Fitting Repeat 4
# weights: 305
initial value 99.587583
iter 10 value 94.280324
iter 20 value 94.213771
iter 30 value 94.185152
iter 40 value 94.178096
iter 50 value 94.169715
final value 94.169653
converged
Fitting Repeat 5
# weights: 305
initial value 100.694354
iter 10 value 94.488441
iter 20 value 94.257594
iter 30 value 87.928984
iter 40 value 87.923344
iter 50 value 87.921889
iter 60 value 87.484915
final value 87.484666
converged
Fitting Repeat 1
# weights: 507
initial value 97.811637
iter 10 value 94.295592
iter 20 value 94.238138
iter 30 value 94.204663
iter 40 value 94.178588
iter 50 value 93.297345
iter 60 value 87.314090
iter 70 value 83.460828
iter 80 value 83.392322
iter 90 value 82.288431
iter 100 value 82.070437
final value 82.070437
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 97.527434
iter 10 value 94.238421
iter 20 value 94.230236
iter 30 value 94.229808
iter 40 value 93.896090
iter 50 value 92.149577
iter 60 value 83.947835
iter 70 value 82.108238
iter 80 value 79.827377
final value 79.798021
converged
Fitting Repeat 3
# weights: 507
initial value 118.691904
iter 10 value 94.494499
iter 20 value 94.408662
iter 30 value 91.200015
iter 40 value 90.044706
iter 50 value 89.870767
iter 60 value 89.860693
iter 70 value 89.860221
iter 80 value 89.859570
final value 89.859542
converged
Fitting Repeat 4
# weights: 507
initial value 97.170051
iter 10 value 94.283598
iter 20 value 94.269720
iter 30 value 84.501284
iter 40 value 83.616507
iter 50 value 83.615782
iter 60 value 83.613519
final value 83.613314
converged
Fitting Repeat 5
# weights: 507
initial value 95.613209
iter 10 value 84.794283
iter 20 value 84.722660
iter 30 value 84.135909
iter 40 value 82.914143
iter 50 value 82.887093
iter 60 value 82.884153
iter 70 value 82.879158
iter 80 value 82.523533
iter 90 value 81.781361
iter 100 value 81.460758
final value 81.460758
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.644927
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.127233
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 105.473225
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 100.114953
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 99.673047
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 103.019210
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 101.966902
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 94.976275
final value 94.309797
converged
Fitting Repeat 4
# weights: 305
initial value 104.955217
final value 94.325945
converged
Fitting Repeat 5
# weights: 305
initial value 104.101010
iter 10 value 94.665802
iter 20 value 94.463209
iter 30 value 94.448515
iter 30 value 94.448515
iter 30 value 94.448515
final value 94.448515
converged
Fitting Repeat 1
# weights: 507
initial value 97.391938
iter 10 value 94.232900
iter 20 value 86.950722
iter 30 value 86.076749
iter 40 value 86.062223
final value 86.062150
converged
Fitting Repeat 2
# weights: 507
initial value 120.058536
iter 10 value 94.475658
iter 20 value 94.325996
final value 94.325945
converged
Fitting Repeat 3
# weights: 507
initial value 95.268973
iter 10 value 94.339997
final value 94.295858
converged
Fitting Repeat 4
# weights: 507
initial value 101.796480
final value 94.466823
converged
Fitting Repeat 5
# weights: 507
initial value 95.420793
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 99.010822
iter 10 value 94.494436
iter 20 value 94.424382
iter 30 value 90.306388
iter 40 value 86.691709
iter 50 value 86.425777
iter 60 value 85.783536
iter 70 value 85.588695
iter 80 value 85.368127
iter 90 value 85.175211
final value 85.175206
converged
Fitting Repeat 2
# weights: 103
initial value 110.621850
iter 10 value 94.488164
iter 20 value 93.162513
iter 30 value 92.742492
iter 40 value 88.187032
iter 50 value 86.245975
iter 60 value 85.544764
iter 70 value 85.309756
iter 80 value 85.175224
final value 85.175206
converged
Fitting Repeat 3
# weights: 103
initial value 103.981132
iter 10 value 94.815389
iter 20 value 93.916835
iter 30 value 87.325381
iter 40 value 86.980197
iter 50 value 85.539453
final value 85.538909
converged
Fitting Repeat 4
# weights: 103
initial value 98.670696
iter 10 value 92.226391
iter 20 value 90.218830
iter 30 value 89.574771
iter 40 value 88.871666
iter 50 value 87.420244
iter 60 value 87.034064
iter 70 value 86.617064
iter 80 value 85.672356
iter 90 value 85.127003
iter 100 value 84.805867
final value 84.805867
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 121.297357
iter 10 value 93.366777
iter 20 value 86.674236
iter 30 value 86.428603
iter 40 value 85.399216
iter 50 value 85.175618
final value 85.175206
converged
Fitting Repeat 1
# weights: 305
initial value 106.060876
iter 10 value 94.819808
iter 20 value 94.430202
iter 30 value 92.443459
iter 40 value 90.507882
iter 50 value 89.021415
iter 60 value 88.584812
iter 70 value 87.679666
iter 80 value 85.322343
iter 90 value 83.973071
iter 100 value 83.292378
final value 83.292378
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 107.749761
iter 10 value 94.350855
iter 20 value 89.028245
iter 30 value 87.574974
iter 40 value 87.294300
iter 50 value 84.656690
iter 60 value 83.913503
iter 70 value 83.742509
iter 80 value 83.621605
iter 90 value 83.545280
iter 100 value 83.418550
final value 83.418550
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.250715
iter 10 value 94.633518
iter 20 value 92.768564
iter 30 value 89.282198
iter 40 value 85.818332
iter 50 value 85.415269
iter 60 value 84.782773
iter 70 value 84.534020
iter 80 value 84.479930
iter 90 value 84.384441
iter 100 value 84.234582
final value 84.234582
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.570968
iter 10 value 94.329330
iter 20 value 89.209722
iter 30 value 85.725827
iter 40 value 85.319329
iter 50 value 84.742799
iter 60 value 84.543351
iter 70 value 84.421407
iter 80 value 84.367929
iter 90 value 83.890127
iter 100 value 82.845930
final value 82.845930
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.027290
iter 10 value 94.109726
iter 20 value 86.368271
iter 30 value 85.790413
iter 40 value 85.293763
iter 50 value 83.362787
iter 60 value 82.597293
iter 70 value 82.079064
iter 80 value 82.018378
iter 90 value 82.002957
iter 100 value 81.968168
final value 81.968168
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 118.586389
iter 10 value 96.537158
iter 20 value 93.907158
iter 30 value 88.509676
iter 40 value 86.568589
iter 50 value 85.944196
iter 60 value 85.176620
iter 70 value 84.677289
iter 80 value 83.363293
iter 90 value 82.540252
iter 100 value 82.044250
final value 82.044250
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.706433
iter 10 value 94.617620
iter 20 value 94.450990
iter 30 value 87.957865
iter 40 value 87.141141
iter 50 value 84.132982
iter 60 value 82.774477
iter 70 value 82.054610
iter 80 value 81.802291
iter 90 value 81.553633
iter 100 value 81.479029
final value 81.479029
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.805698
iter 10 value 93.114541
iter 20 value 88.067693
iter 30 value 86.354020
iter 40 value 84.620265
iter 50 value 83.547905
iter 60 value 83.389080
iter 70 value 83.216929
iter 80 value 83.012738
iter 90 value 82.671809
iter 100 value 82.273033
final value 82.273033
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.675491
iter 10 value 94.505280
iter 20 value 94.186933
iter 30 value 93.988495
iter 40 value 91.749910
iter 50 value 88.723470
iter 60 value 87.710982
iter 70 value 85.988835
iter 80 value 84.914541
iter 90 value 84.149217
iter 100 value 82.746486
final value 82.746486
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.182476
iter 10 value 94.516358
iter 20 value 92.984880
iter 30 value 87.561081
iter 40 value 86.722092
iter 50 value 85.236429
iter 60 value 84.232233
iter 70 value 83.939223
iter 80 value 83.568718
iter 90 value 82.904901
iter 100 value 82.175918
final value 82.175918
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.832173
final value 94.485785
converged
Fitting Repeat 2
# weights: 103
initial value 105.171786
final value 94.485769
converged
Fitting Repeat 3
# weights: 103
initial value 95.214118
final value 94.485814
converged
Fitting Repeat 4
# weights: 103
initial value 96.830212
final value 94.485739
converged
Fitting Repeat 5
# weights: 103
initial value 109.810928
final value 94.485863
converged
Fitting Repeat 1
# weights: 305
initial value 103.225778
iter 10 value 94.471715
iter 20 value 93.958990
iter 30 value 91.119172
iter 40 value 90.573590
iter 50 value 88.679664
iter 60 value 86.650103
iter 70 value 84.630077
iter 80 value 83.402471
iter 90 value 82.866399
iter 100 value 82.820282
final value 82.820282
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.252163
iter 10 value 94.331058
iter 20 value 94.326625
iter 30 value 93.722134
iter 40 value 86.020872
iter 50 value 85.826936
iter 60 value 85.554643
final value 85.554550
converged
Fitting Repeat 3
# weights: 305
initial value 128.968048
iter 10 value 94.490176
iter 20 value 94.479949
iter 30 value 86.777222
iter 40 value 85.667085
iter 50 value 85.664392
iter 60 value 85.663689
iter 60 value 85.663689
iter 60 value 85.663689
final value 85.663689
converged
Fitting Repeat 4
# weights: 305
initial value 94.837841
iter 10 value 94.485451
iter 20 value 94.483124
iter 30 value 86.419625
iter 40 value 85.606960
final value 85.439704
converged
Fitting Repeat 5
# weights: 305
initial value 96.279039
iter 10 value 94.472020
iter 20 value 94.252277
iter 30 value 86.657197
iter 40 value 86.644013
iter 50 value 86.618472
iter 60 value 86.611690
iter 70 value 86.138218
iter 80 value 85.829893
final value 85.827188
converged
Fitting Repeat 1
# weights: 507
initial value 103.015086
iter 10 value 94.492150
iter 20 value 94.477715
iter 30 value 89.159060
iter 40 value 86.068196
iter 50 value 85.447118
iter 60 value 85.144771
iter 70 value 85.143286
iter 80 value 85.139990
iter 90 value 84.573110
iter 100 value 83.667203
final value 83.667203
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 100.233531
iter 10 value 94.493200
iter 20 value 94.485597
final value 94.484684
converged
Fitting Repeat 3
# weights: 507
initial value 107.148721
iter 10 value 94.474394
iter 20 value 93.455205
iter 30 value 92.489570
iter 40 value 85.933165
iter 50 value 85.640127
iter 60 value 84.662696
iter 70 value 84.116637
final value 84.116627
converged
Fitting Repeat 4
# weights: 507
initial value 112.895658
iter 10 value 94.188668
iter 20 value 90.372681
iter 30 value 90.043245
iter 40 value 90.036689
iter 40 value 90.036689
final value 90.036689
converged
Fitting Repeat 5
# weights: 507
initial value 107.448254
iter 10 value 94.492385
iter 20 value 94.436672
iter 30 value 86.873955
iter 40 value 86.255411
iter 50 value 85.657456
iter 60 value 83.977290
iter 70 value 83.653567
iter 80 value 82.050908
iter 90 value 81.266919
iter 100 value 81.215596
final value 81.215596
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.306430
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.753852
final value 94.026542
converged
Fitting Repeat 3
# weights: 103
initial value 95.830293
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 99.347340
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 97.834118
iter 10 value 90.605973
iter 20 value 90.444444
iter 20 value 90.444444
iter 20 value 90.444444
final value 90.444444
converged
Fitting Repeat 1
# weights: 305
initial value 102.558040
iter 10 value 94.026543
iter 10 value 94.026542
iter 10 value 94.026542
final value 94.026542
converged
Fitting Repeat 2
# weights: 305
initial value 96.420645
iter 10 value 92.983415
iter 20 value 91.533642
iter 30 value 91.382300
iter 40 value 91.381642
final value 91.381640
converged
Fitting Repeat 3
# weights: 305
initial value 109.724282
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 102.566892
final value 94.026542
converged
Fitting Repeat 5
# weights: 305
initial value 110.926711
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 98.336260
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 108.084303
iter 10 value 93.829784
iter 20 value 93.335260
iter 30 value 93.103968
final value 93.103897
converged
Fitting Repeat 3
# weights: 507
initial value 96.954226
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 105.499059
iter 10 value 94.026546
final value 94.026542
converged
Fitting Repeat 5
# weights: 507
initial value 107.822205
final value 94.026542
converged
Fitting Repeat 1
# weights: 103
initial value 106.276290
iter 10 value 94.469591
iter 20 value 94.216631
iter 30 value 94.214390
iter 40 value 94.190411
iter 50 value 85.872443
iter 60 value 84.544195
iter 70 value 83.860422
iter 80 value 83.742128
final value 83.742010
converged
Fitting Repeat 2
# weights: 103
initial value 97.269067
iter 10 value 94.145489
iter 20 value 92.087848
iter 30 value 91.990513
iter 40 value 84.874574
iter 50 value 84.606765
iter 60 value 84.309769
iter 70 value 83.963888
iter 80 value 83.302497
iter 90 value 83.215638
iter 100 value 83.214324
final value 83.214324
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 102.692018
iter 10 value 94.488624
iter 20 value 94.230988
iter 30 value 94.140803
iter 40 value 94.102671
iter 50 value 93.013979
iter 60 value 89.870734
iter 70 value 89.676495
iter 80 value 89.560537
iter 90 value 89.555316
iter 90 value 89.555316
iter 90 value 89.555316
final value 89.555316
converged
Fitting Repeat 4
# weights: 103
initial value 100.341127
iter 10 value 89.462269
iter 20 value 85.636903
iter 30 value 85.335943
iter 40 value 84.285479
iter 50 value 83.998122
iter 60 value 83.980107
final value 83.979675
converged
Fitting Repeat 5
# weights: 103
initial value 96.398903
iter 10 value 94.483971
iter 20 value 86.202820
iter 30 value 85.563455
iter 40 value 85.340646
iter 50 value 84.260400
iter 60 value 83.980187
final value 83.979675
converged
Fitting Repeat 1
# weights: 305
initial value 126.023277
iter 10 value 95.151763
iter 20 value 90.097350
iter 30 value 89.434398
iter 40 value 87.141855
iter 50 value 82.341123
iter 60 value 81.658853
iter 70 value 80.613531
iter 80 value 80.275096
iter 90 value 80.141283
iter 100 value 79.978836
final value 79.978836
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.599725
iter 10 value 94.506399
iter 20 value 87.399962
iter 30 value 85.460989
iter 40 value 85.120003
iter 50 value 83.711585
iter 60 value 83.670164
iter 70 value 83.541404
iter 80 value 82.737207
iter 90 value 81.211059
iter 100 value 80.948367
final value 80.948367
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.168655
iter 10 value 94.301503
iter 20 value 87.256905
iter 30 value 84.644818
iter 40 value 84.043115
iter 50 value 83.773916
iter 60 value 83.683859
iter 70 value 83.626490
iter 80 value 82.728275
iter 90 value 81.923056
iter 100 value 81.726146
final value 81.726146
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.149914
iter 10 value 95.432033
iter 20 value 91.151244
iter 30 value 87.388450
iter 40 value 82.996345
iter 50 value 81.405329
iter 60 value 80.881042
iter 70 value 80.810913
iter 80 value 80.636062
iter 90 value 80.412121
iter 100 value 80.169145
final value 80.169145
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.391347
iter 10 value 94.044475
iter 20 value 86.091592
iter 30 value 85.278456
iter 40 value 84.769623
iter 50 value 84.396125
iter 60 value 82.586197
iter 70 value 81.744080
iter 80 value 81.434267
iter 90 value 81.235995
iter 100 value 80.741379
final value 80.741379
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.000532
iter 10 value 94.200755
iter 20 value 86.541330
iter 30 value 84.198427
iter 40 value 82.473839
iter 50 value 82.238701
iter 60 value 81.736945
iter 70 value 81.571290
iter 80 value 81.485382
iter 90 value 80.654297
iter 100 value 80.226060
final value 80.226060
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.167658
iter 10 value 93.723177
iter 20 value 85.276575
iter 30 value 84.156642
iter 40 value 83.434605
iter 50 value 82.364401
iter 60 value 81.326475
iter 70 value 80.895041
iter 80 value 80.835378
iter 90 value 80.801365
iter 100 value 80.778362
final value 80.778362
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.484837
iter 10 value 96.044710
iter 20 value 91.949346
iter 30 value 83.872489
iter 40 value 83.637781
iter 50 value 83.611232
iter 60 value 83.518682
iter 70 value 82.355348
iter 80 value 81.491664
iter 90 value 81.378005
iter 100 value 81.059066
final value 81.059066
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 116.483067
iter 10 value 94.419403
iter 20 value 88.089696
iter 30 value 84.821069
iter 40 value 81.431918
iter 50 value 80.778858
iter 60 value 80.376471
iter 70 value 80.066241
iter 80 value 79.730916
iter 90 value 79.693744
iter 100 value 79.613864
final value 79.613864
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.675878
iter 10 value 93.763331
iter 20 value 84.924849
iter 30 value 81.591001
iter 40 value 80.682605
iter 50 value 80.217885
iter 60 value 79.781162
iter 70 value 79.681741
iter 80 value 79.636352
iter 90 value 79.498598
iter 100 value 79.436867
final value 79.436867
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.806024
final value 94.485969
converged
Fitting Repeat 2
# weights: 103
initial value 101.013488
iter 10 value 94.485790
iter 20 value 94.450340
iter 30 value 93.119330
final value 93.110531
converged
Fitting Repeat 3
# weights: 103
initial value 101.832794
final value 93.111717
converged
Fitting Repeat 4
# weights: 103
initial value 96.881337
iter 10 value 94.485928
iter 20 value 94.470654
iter 30 value 90.638551
iter 40 value 85.204277
iter 50 value 84.739983
final value 84.739813
converged
Fitting Repeat 5
# weights: 103
initial value 103.041934
final value 94.485714
converged
Fitting Repeat 1
# weights: 305
initial value 98.388268
iter 10 value 94.489313
iter 20 value 87.233047
iter 30 value 87.150571
iter 40 value 86.698416
iter 50 value 86.506995
iter 60 value 86.505696
iter 70 value 86.505552
iter 80 value 86.500107
final value 86.499951
converged
Fitting Repeat 2
# weights: 305
initial value 111.969197
iter 10 value 94.363487
iter 20 value 94.343375
iter 30 value 94.063190
iter 40 value 94.028195
iter 50 value 93.848724
iter 60 value 92.511798
iter 70 value 90.464522
iter 80 value 90.342624
iter 90 value 90.340788
iter 100 value 90.340607
final value 90.340607
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 94.496219
final value 94.488856
converged
Fitting Repeat 4
# weights: 305
initial value 102.295986
iter 10 value 94.489384
iter 20 value 94.464054
iter 30 value 91.287035
iter 40 value 91.126623
iter 50 value 90.845286
final value 90.845284
converged
Fitting Repeat 5
# weights: 305
initial value 101.233670
iter 10 value 94.031672
iter 20 value 94.026954
iter 30 value 94.026690
iter 40 value 86.196153
iter 50 value 86.039422
iter 60 value 84.746775
iter 70 value 84.721146
iter 80 value 84.706444
iter 90 value 84.705606
iter 100 value 84.705299
final value 84.705299
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 99.325313
iter 10 value 92.484160
iter 20 value 86.953753
iter 30 value 86.952576
iter 40 value 85.893797
iter 50 value 82.936952
iter 60 value 82.323454
iter 70 value 82.269067
iter 80 value 80.872273
iter 90 value 80.169077
iter 100 value 79.561327
final value 79.561327
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.983210
iter 10 value 94.348557
iter 20 value 94.232955
iter 30 value 94.028824
iter 40 value 94.027158
final value 94.027157
converged
Fitting Repeat 3
# weights: 507
initial value 106.215119
iter 10 value 88.798386
iter 20 value 86.385382
iter 30 value 86.225862
iter 40 value 85.826181
iter 50 value 85.806923
iter 60 value 85.802756
iter 70 value 85.799755
final value 85.799443
converged
Fitting Repeat 4
# weights: 507
initial value 106.227548
iter 10 value 94.491526
iter 20 value 94.475026
iter 30 value 88.383411
iter 40 value 87.380409
iter 50 value 81.641829
iter 60 value 80.543550
iter 70 value 80.309099
iter 80 value 80.305316
iter 90 value 80.304772
iter 100 value 80.298204
final value 80.298204
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 100.175295
iter 10 value 94.492098
iter 20 value 94.226088
iter 30 value 92.939330
iter 40 value 88.347060
iter 50 value 86.793430
iter 60 value 81.131399
iter 70 value 80.751580
final value 80.750294
converged
Fitting Repeat 1
# weights: 103
initial value 101.865145
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 95.183895
final value 94.052911
converged
Fitting Repeat 3
# weights: 103
initial value 99.180832
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 108.398754
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 97.203750
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 102.914437
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 103.935739
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 94.388777
iter 10 value 92.826038
iter 10 value 92.826038
iter 10 value 92.826038
final value 92.826038
converged
Fitting Repeat 4
# weights: 305
initial value 107.450516
final value 93.836066
converged
Fitting Repeat 5
# weights: 305
initial value 101.674086
iter 10 value 93.838571
final value 93.836066
converged
Fitting Repeat 1
# weights: 507
initial value 96.698106
iter 10 value 93.328844
final value 93.328261
converged
Fitting Repeat 2
# weights: 507
initial value 115.556158
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 99.614554
final value 92.826036
converged
Fitting Repeat 4
# weights: 507
initial value 100.362491
final value 93.482759
converged
Fitting Repeat 5
# weights: 507
initial value 113.476508
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 100.994538
iter 10 value 94.201822
iter 20 value 94.057331
iter 30 value 94.042521
iter 40 value 92.429379
iter 50 value 91.772414
iter 60 value 90.352842
iter 70 value 89.882318
iter 80 value 89.443219
final value 89.442848
converged
Fitting Repeat 2
# weights: 103
initial value 101.245956
iter 10 value 94.058595
iter 20 value 93.270180
iter 30 value 92.935962
iter 40 value 90.447774
iter 50 value 85.838688
iter 60 value 83.454763
iter 70 value 82.792376
iter 80 value 82.240783
iter 90 value 81.369404
iter 100 value 81.073349
final value 81.073349
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 112.494967
iter 10 value 94.073868
iter 20 value 93.970147
iter 30 value 93.266668
iter 40 value 92.945708
iter 50 value 92.029674
iter 60 value 89.134181
iter 70 value 87.958156
iter 80 value 87.520108
iter 90 value 85.986542
iter 100 value 84.026059
final value 84.026059
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.828665
iter 10 value 94.051084
iter 20 value 93.903536
iter 30 value 93.897415
iter 40 value 93.569621
iter 50 value 84.708824
iter 60 value 83.976132
iter 70 value 83.645796
iter 80 value 83.588854
final value 83.588814
converged
Fitting Repeat 5
# weights: 103
initial value 102.570497
iter 10 value 94.082420
iter 20 value 94.048621
iter 30 value 93.016196
iter 40 value 90.754435
iter 50 value 83.859367
iter 60 value 83.202352
iter 70 value 82.285766
iter 80 value 81.850452
iter 90 value 81.775376
iter 100 value 81.714537
final value 81.714537
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 99.802939
iter 10 value 94.094769
iter 20 value 93.933895
iter 30 value 92.018529
iter 40 value 91.368668
iter 50 value 84.397633
iter 60 value 82.944295
iter 70 value 81.238735
iter 80 value 80.733796
iter 90 value 80.581394
iter 100 value 80.538075
final value 80.538075
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 132.145195
iter 10 value 97.930685
iter 20 value 94.044832
iter 30 value 87.457425
iter 40 value 86.666798
iter 50 value 82.365350
iter 60 value 80.264521
iter 70 value 79.943497
iter 80 value 79.569559
iter 90 value 79.279213
iter 100 value 79.203536
final value 79.203536
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.742586
iter 10 value 94.081349
iter 20 value 92.111620
iter 30 value 86.865535
iter 40 value 86.006465
iter 50 value 85.771339
iter 60 value 85.532469
iter 70 value 84.488782
iter 80 value 82.123194
iter 90 value 81.170525
iter 100 value 81.011350
final value 81.011350
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.734378
iter 10 value 94.243494
iter 20 value 85.604231
iter 30 value 83.797503
iter 40 value 82.648481
iter 50 value 82.437767
iter 60 value 82.358623
iter 70 value 82.062031
iter 80 value 80.440173
iter 90 value 79.226750
iter 100 value 79.050702
final value 79.050702
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 111.789327
iter 10 value 94.060191
iter 20 value 84.488900
iter 30 value 83.491049
iter 40 value 83.350927
iter 50 value 82.026373
iter 60 value 80.603159
iter 70 value 79.918651
iter 80 value 79.150662
iter 90 value 79.083424
iter 100 value 79.044751
final value 79.044751
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.869366
iter 10 value 90.079045
iter 20 value 84.413260
iter 30 value 83.419877
iter 40 value 81.433990
iter 50 value 80.758717
iter 60 value 80.679790
iter 70 value 80.373494
iter 80 value 80.135963
iter 90 value 80.119174
iter 100 value 79.868113
final value 79.868113
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.292912
iter 10 value 93.766550
iter 20 value 87.699152
iter 30 value 84.616820
iter 40 value 82.898718
iter 50 value 80.894871
iter 60 value 79.704661
iter 70 value 79.105350
iter 80 value 79.073148
iter 90 value 79.048782
iter 100 value 79.041243
final value 79.041243
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 116.546593
iter 10 value 93.997834
iter 20 value 85.038235
iter 30 value 84.075089
iter 40 value 83.340343
iter 50 value 82.680342
iter 60 value 81.483666
iter 70 value 79.347978
iter 80 value 78.996753
iter 90 value 78.895960
iter 100 value 78.838104
final value 78.838104
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 131.836759
iter 10 value 93.947584
iter 20 value 89.283736
iter 30 value 84.588122
iter 40 value 82.854358
iter 50 value 82.352523
iter 60 value 82.179485
iter 70 value 81.256469
iter 80 value 79.894175
iter 90 value 79.332725
iter 100 value 79.191840
final value 79.191840
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.366878
iter 10 value 94.400928
iter 20 value 93.327516
iter 30 value 92.927016
iter 40 value 91.970371
iter 50 value 84.031427
iter 60 value 82.330028
iter 70 value 81.567858
iter 80 value 80.266366
iter 90 value 79.479954
iter 100 value 78.799183
final value 78.799183
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.704748
final value 94.054545
converged
Fitting Repeat 2
# weights: 103
initial value 96.764878
iter 10 value 94.054392
iter 20 value 94.022584
final value 93.836194
converged
Fitting Repeat 3
# weights: 103
initial value 107.260478
iter 10 value 94.054657
iter 20 value 94.053000
iter 30 value 92.879757
final value 92.826353
converged
Fitting Repeat 4
# weights: 103
initial value 94.030768
iter 10 value 93.837859
iter 20 value 93.678466
iter 30 value 90.737608
iter 40 value 89.335673
iter 50 value 89.290000
iter 60 value 88.828154
iter 70 value 88.759547
final value 88.759540
converged
Fitting Repeat 5
# weights: 103
initial value 96.482898
final value 94.054526
converged
Fitting Repeat 1
# weights: 305
initial value 95.280977
iter 10 value 94.057168
iter 20 value 82.696341
iter 30 value 81.330916
iter 40 value 81.324083
iter 50 value 81.284352
iter 60 value 81.278372
iter 70 value 81.268067
iter 80 value 81.158927
iter 90 value 80.675829
iter 100 value 80.000444
final value 80.000444
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.977497
iter 10 value 94.055482
iter 20 value 93.972337
iter 30 value 83.674886
iter 40 value 83.671680
iter 50 value 83.214193
iter 60 value 83.199664
iter 70 value 82.189360
iter 80 value 82.173503
final value 82.170565
converged
Fitting Repeat 3
# weights: 305
initial value 95.986119
iter 10 value 94.054439
iter 20 value 93.249117
iter 30 value 89.300421
iter 40 value 89.295276
iter 50 value 89.292404
final value 89.292362
converged
Fitting Repeat 4
# weights: 305
initial value 100.917604
iter 10 value 94.057603
iter 20 value 94.052911
iter 30 value 83.766540
final value 83.671542
converged
Fitting Repeat 5
# weights: 305
initial value 95.369153
iter 10 value 94.057679
iter 20 value 94.038146
iter 30 value 87.982652
iter 40 value 82.813216
final value 82.810353
converged
Fitting Repeat 1
# weights: 507
initial value 116.136907
iter 10 value 94.061144
iter 20 value 93.861819
iter 30 value 83.781730
iter 40 value 83.775179
iter 50 value 83.760662
iter 60 value 83.744688
iter 70 value 83.711343
iter 80 value 83.279636
iter 90 value 82.433818
iter 100 value 79.755986
final value 79.755986
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 108.289350
iter 10 value 94.061343
iter 20 value 93.921887
iter 30 value 92.826447
final value 92.826386
converged
Fitting Repeat 3
# weights: 507
initial value 119.688973
iter 10 value 94.060995
iter 20 value 93.675380
iter 30 value 92.826327
iter 40 value 91.899616
iter 50 value 85.480403
iter 60 value 82.955531
iter 70 value 80.782864
iter 80 value 80.257323
iter 90 value 80.071737
iter 100 value 80.051017
final value 80.051017
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 102.082777
iter 10 value 93.335946
iter 20 value 93.329934
iter 30 value 91.512631
iter 40 value 86.421477
iter 50 value 86.403182
iter 60 value 86.402165
iter 70 value 84.700029
iter 80 value 84.301352
iter 90 value 83.786038
iter 100 value 83.756533
final value 83.756533
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 106.704284
iter 10 value 94.061350
iter 20 value 94.053024
iter 30 value 94.036070
iter 40 value 92.493223
iter 50 value 87.056601
iter 60 value 86.894990
iter 70 value 86.794695
iter 80 value 86.791918
iter 80 value 86.791918
final value 86.791918
converged
Fitting Repeat 1
# weights: 103
initial value 94.623124
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.631522
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 112.165323
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 99.397292
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 108.623497
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 97.922679
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 96.515517
final value 94.038251
converged
Fitting Repeat 3
# weights: 305
initial value 96.685207
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 94.946344
final value 94.038251
converged
Fitting Repeat 5
# weights: 305
initial value 107.372416
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 97.578077
final value 94.038251
converged
Fitting Repeat 2
# weights: 507
initial value 96.714270
final value 93.962011
converged
Fitting Repeat 3
# weights: 507
initial value 99.395871
final value 93.962011
converged
Fitting Repeat 4
# weights: 507
initial value 105.411737
final value 93.869755
converged
Fitting Repeat 5
# weights: 507
initial value 103.062326
iter 10 value 86.702780
iter 20 value 85.525832
iter 30 value 84.755853
final value 84.755832
converged
Fitting Repeat 1
# weights: 103
initial value 116.292195
iter 10 value 94.051552
iter 20 value 93.604533
iter 30 value 88.492741
iter 40 value 86.986121
iter 50 value 85.281114
iter 60 value 84.592944
iter 70 value 83.708251
iter 80 value 82.047383
iter 90 value 81.789195
iter 100 value 81.444337
final value 81.444337
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 100.872162
iter 10 value 93.826663
iter 20 value 86.961844
iter 30 value 86.487080
iter 40 value 85.662162
iter 50 value 84.291471
iter 60 value 84.169687
iter 70 value 84.007718
iter 80 value 83.951868
final value 83.950799
converged
Fitting Repeat 3
# weights: 103
initial value 115.742129
iter 10 value 93.890061
iter 20 value 85.593046
iter 30 value 84.944539
iter 40 value 84.636751
iter 50 value 84.442926
iter 60 value 84.425387
iter 70 value 83.554562
iter 80 value 83.464169
final value 83.463415
converged
Fitting Repeat 4
# weights: 103
initial value 97.598531
iter 10 value 94.057450
iter 20 value 93.827665
iter 30 value 92.738996
iter 40 value 85.403769
iter 50 value 84.915908
iter 60 value 84.629093
iter 70 value 83.705118
iter 80 value 83.469403
iter 90 value 83.463494
final value 83.463417
converged
Fitting Repeat 5
# weights: 103
initial value 98.957406
iter 10 value 94.054788
iter 20 value 88.564471
iter 30 value 87.008957
iter 40 value 85.749132
iter 50 value 84.310495
iter 60 value 84.282044
final value 84.282043
converged
Fitting Repeat 1
# weights: 305
initial value 102.550540
iter 10 value 94.886197
iter 20 value 92.184777
iter 30 value 85.812639
iter 40 value 83.146482
iter 50 value 81.248105
iter 60 value 80.387607
iter 70 value 80.067705
iter 80 value 79.714684
iter 90 value 79.419898
iter 100 value 79.261938
final value 79.261938
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 110.155255
iter 10 value 94.054435
iter 20 value 91.724962
iter 30 value 85.041499
iter 40 value 83.340267
iter 50 value 83.055613
iter 60 value 82.204420
iter 70 value 82.032648
iter 80 value 81.595718
iter 90 value 80.412093
iter 100 value 79.497505
final value 79.497505
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.090615
iter 10 value 93.989596
iter 20 value 88.377036
iter 30 value 85.094055
iter 40 value 84.173674
iter 50 value 83.988600
iter 60 value 83.877673
iter 70 value 81.751903
iter 80 value 81.299194
iter 90 value 80.782938
iter 100 value 80.694488
final value 80.694488
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 110.169198
iter 10 value 93.988094
iter 20 value 88.304827
iter 30 value 84.322780
iter 40 value 83.582451
iter 50 value 83.313328
iter 60 value 82.415314
iter 70 value 81.549118
iter 80 value 81.237814
iter 90 value 81.005745
iter 100 value 80.914345
final value 80.914345
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 100.427047
iter 10 value 93.924674
iter 20 value 85.169777
iter 30 value 84.652196
iter 40 value 83.945706
iter 50 value 82.917107
iter 60 value 82.805293
iter 70 value 82.643028
iter 80 value 82.540117
iter 90 value 81.986876
iter 100 value 81.413451
final value 81.413451
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 128.397137
iter 10 value 94.141915
iter 20 value 93.406285
iter 30 value 92.312260
iter 40 value 88.030066
iter 50 value 84.815461
iter 60 value 83.731186
iter 70 value 82.126672
iter 80 value 81.415747
iter 90 value 81.108198
iter 100 value 80.868091
final value 80.868091
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.225539
iter 10 value 85.821238
iter 20 value 84.397993
iter 30 value 83.941305
iter 40 value 83.895406
iter 50 value 82.764404
iter 60 value 81.409337
iter 70 value 81.059111
iter 80 value 80.695050
iter 90 value 80.456707
iter 100 value 80.361136
final value 80.361136
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 102.962284
iter 10 value 94.064938
iter 20 value 92.974000
iter 30 value 89.416117
iter 40 value 86.569250
iter 50 value 83.602405
iter 60 value 81.835623
iter 70 value 80.808956
iter 80 value 80.562908
iter 90 value 79.557731
iter 100 value 79.215564
final value 79.215564
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 113.574461
iter 10 value 94.347466
iter 20 value 88.669152
iter 30 value 84.511539
iter 40 value 83.828039
iter 50 value 83.516662
iter 60 value 82.229558
iter 70 value 81.613236
iter 80 value 81.028591
iter 90 value 80.303613
iter 100 value 79.904156
final value 79.904156
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 123.327870
iter 10 value 87.542157
iter 20 value 84.860003
iter 30 value 83.482326
iter 40 value 81.410405
iter 50 value 80.916202
iter 60 value 80.398112
iter 70 value 79.960849
iter 80 value 79.875469
iter 90 value 79.591850
iter 100 value 79.462851
final value 79.462851
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.104709
iter 10 value 92.831510
iter 20 value 88.058238
iter 30 value 85.882352
iter 40 value 85.881798
iter 50 value 85.855289
iter 60 value 85.740530
iter 70 value 85.740390
final value 85.740215
converged
Fitting Repeat 2
# weights: 103
initial value 101.565893
final value 94.054539
converged
Fitting Repeat 3
# weights: 103
initial value 97.085105
iter 10 value 94.039826
iter 20 value 93.838995
final value 93.764104
converged
Fitting Repeat 4
# weights: 103
initial value 101.215665
final value 94.054494
converged
Fitting Repeat 5
# weights: 103
initial value 99.705143
final value 94.054721
converged
Fitting Repeat 1
# weights: 305
initial value 95.614164
iter 10 value 94.055337
iter 20 value 94.036212
iter 30 value 93.423841
iter 40 value 92.922393
iter 50 value 90.308598
iter 60 value 84.108229
iter 70 value 83.383064
iter 80 value 83.379257
iter 90 value 82.615215
final value 82.614517
converged
Fitting Repeat 2
# weights: 305
initial value 98.599355
iter 10 value 93.921180
iter 20 value 93.677734
iter 30 value 93.674519
iter 40 value 93.674304
iter 50 value 93.669509
iter 60 value 93.455747
iter 70 value 83.295367
iter 80 value 83.273640
iter 90 value 83.271940
iter 100 value 83.269512
final value 83.269512
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.303946
iter 10 value 94.057557
iter 20 value 88.384573
iter 30 value 87.049824
iter 40 value 87.038536
final value 87.037907
converged
Fitting Repeat 4
# weights: 305
initial value 98.170531
iter 10 value 94.059372
iter 20 value 93.544560
iter 30 value 90.431121
iter 40 value 90.251014
iter 50 value 89.609917
iter 60 value 86.936710
iter 70 value 85.288831
iter 80 value 84.643443
iter 90 value 84.642321
iter 100 value 83.996006
final value 83.996006
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 113.280286
iter 10 value 94.056691
iter 20 value 94.032348
iter 30 value 93.579683
iter 40 value 87.906200
iter 50 value 80.995690
iter 60 value 80.536123
iter 70 value 80.501385
final value 80.501214
converged
Fitting Repeat 1
# weights: 507
initial value 103.348667
iter 10 value 94.047165
iter 20 value 93.994465
iter 30 value 93.400974
iter 40 value 92.415309
iter 50 value 92.313524
final value 92.313066
converged
Fitting Repeat 2
# weights: 507
initial value 99.753020
iter 10 value 94.046211
iter 20 value 93.949819
iter 30 value 87.796959
iter 40 value 82.104512
iter 50 value 79.441810
iter 60 value 79.241745
iter 70 value 78.986766
iter 80 value 78.864821
iter 90 value 78.851104
final value 78.850473
converged
Fitting Repeat 3
# weights: 507
initial value 132.872601
iter 10 value 93.915770
iter 20 value 93.580231
iter 30 value 93.457553
iter 40 value 93.455227
iter 50 value 93.363828
iter 60 value 93.345007
iter 70 value 91.874642
iter 80 value 85.241243
iter 90 value 83.181566
iter 100 value 83.172381
final value 83.172381
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 100.235841
iter 10 value 94.060383
iter 20 value 93.937599
iter 30 value 93.531618
iter 40 value 93.454123
final value 93.453773
converged
Fitting Repeat 5
# weights: 507
initial value 97.751324
iter 10 value 94.047207
iter 20 value 94.039748
iter 30 value 94.039121
iter 40 value 88.413083
iter 50 value 83.089439
iter 60 value 80.131619
iter 70 value 79.111036
iter 80 value 78.411512
iter 90 value 78.186571
iter 100 value 77.949589
final value 77.949589
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 152.391476
iter 10 value 117.767159
iter 20 value 117.761282
final value 117.760511
converged
Fitting Repeat 2
# weights: 507
initial value 137.556303
iter 10 value 117.185230
iter 20 value 109.893791
iter 30 value 109.480476
iter 40 value 107.103119
iter 50 value 104.189233
iter 60 value 103.878923
iter 70 value 103.795323
iter 80 value 103.760763
final value 103.760592
converged
Fitting Repeat 3
# weights: 507
initial value 123.667894
iter 10 value 117.898257
iter 20 value 117.766706
iter 30 value 117.759236
iter 40 value 115.248361
final value 108.506935
converged
Fitting Repeat 4
# weights: 507
initial value 120.729370
iter 10 value 117.095669
iter 20 value 116.883496
iter 30 value 116.848482
iter 40 value 116.846539
iter 50 value 116.842739
iter 60 value 109.154700
iter 70 value 109.043303
iter 80 value 107.599758
iter 90 value 106.820054
iter 100 value 106.818988
final value 106.818988
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 122.678068
iter 10 value 117.898172
iter 20 value 114.557304
iter 30 value 107.970951
iter 40 value 107.797369
iter 50 value 107.795089
iter 60 value 105.728727
iter 70 value 105.170892
iter 80 value 105.086891
iter 90 value 104.375497
iter 100 value 101.944451
final value 101.944451
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Mon Feb 23 00:48:29 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
42.525 1.328 92.595
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.263 | 0.428 | 33.775 | |
| FreqInteractors | 0.428 | 0.019 | 0.448 | |
| calculateAAC | 0.028 | 0.001 | 0.030 | |
| calculateAutocor | 0.299 | 0.009 | 0.309 | |
| calculateCTDC | 0.070 | 0.001 | 0.071 | |
| calculateCTDD | 0.507 | 0.006 | 0.513 | |
| calculateCTDT | 0.181 | 0.007 | 0.189 | |
| calculateCTriad | 0.363 | 0.004 | 0.367 | |
| calculateDC | 0.083 | 0.000 | 0.083 | |
| calculateF | 0.306 | 0.001 | 0.307 | |
| calculateKSAAP | 0.097 | 0.001 | 0.099 | |
| calculateQD_Sm | 1.506 | 0.010 | 1.516 | |
| calculateTC | 1.467 | 0.030 | 1.498 | |
| calculateTC_Sm | 0.247 | 0.004 | 0.251 | |
| corr_plot | 34.248 | 0.472 | 34.776 | |
| enrichfindP | 0.491 | 0.038 | 12.781 | |
| enrichfind_hp | 0.058 | 0.004 | 0.893 | |
| enrichplot | 0.513 | 0.001 | 0.515 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.353 | 0.028 | 3.334 | |
| getHPI | 0.000 | 0.000 | 0.001 | |
| get_negativePPI | 0.001 | 0.000 | 0.001 | |
| get_positivePPI | 0.001 | 0.000 | 0.000 | |
| impute_missing_data | 0.001 | 0.000 | 0.001 | |
| plotPPI | 0.077 | 0.002 | 0.078 | |
| pred_ensembel | 12.532 | 0.096 | 11.364 | |
| var_imp | 32.984 | 0.559 | 33.544 | |