Matineh Rahmatbakhsh
| Snapshot Date: 2026-04-23 13:45 -0400 (Thu, 23 Apr 2026) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: devel |
| git_last_commit: 68bd9a1 |
| git_last_commit_date: 2025-12-28 18:34:02 -0400 (Sun, 28 Dec 2025) |
| Back to Build/check report for BioC 3.24: simplified long |
|
This page was generated on 2026-04-24 11:33 -0400 (Fri, 24 Apr 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.4 LTS) | x86_64 | 4.6.0 RC (2026-04-17 r89917) -- "Because it was There" | 4800 |
| 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 1000/2351 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.17.2 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.4 LTS) / x86_64 | OK | OK | OK | | ||||||||
| See other builds for HPiP in R Universe. | ||||||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.17.2 |
| Command: /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings HPiP_1.17.2.tar.gz |
| StartedAt: 2026-04-24 00:26:08 -0400 (Fri, 24 Apr 2026) |
| EndedAt: 2026-04-24 00:41:29 -0400 (Fri, 24 Apr 2026) |
| EllapsedTime: 921.3 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.24-bioc/R/site-library --timings HPiP_1.17.2.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.24-bioc/meat/HPiP.Rcheck’
* using R version 4.6.0 RC (2026-04-17 r89917)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-04-24 04:26:08 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
var_imp 34.483 0.534 35.095
corr_plot 34.281 0.370 34.690
FSmethod 33.771 0.485 34.319
pred_ensembel 13.085 0.385 12.224
enrichfindP 0.516 0.042 9.648
* 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-3.24-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.24-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.24-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.17.2’ ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.6.0 RC (2026-04-17 r89917) -- "Because it was There"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 99.592895
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.559194
final value 94.484216
converged
Fitting Repeat 3
# weights: 103
initial value 95.816034
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 99.635341
iter 10 value 93.463837
iter 20 value 93.136141
iter 30 value 91.391831
iter 40 value 91.378675
final value 91.378516
converged
Fitting Repeat 5
# weights: 103
initial value 96.434466
iter 10 value 93.815112
iter 20 value 93.616681
iter 30 value 93.614914
final value 93.614910
converged
Fitting Repeat 1
# weights: 305
initial value 96.713053
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 95.620928
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 108.098467
final value 94.467391
converged
Fitting Repeat 4
# weights: 305
initial value 106.025194
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 102.270508
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 113.571591
final value 94.467391
converged
Fitting Repeat 2
# weights: 507
initial value 95.435666
iter 10 value 86.752735
iter 20 value 85.957409
iter 30 value 84.970593
iter 40 value 84.773230
final value 84.772435
converged
Fitting Repeat 3
# weights: 507
initial value 99.311182
iter 10 value 92.754641
iter 20 value 91.823079
iter 20 value 91.823079
iter 20 value 91.823079
final value 91.823079
converged
Fitting Repeat 4
# weights: 507
initial value 105.679887
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 98.591522
iter 10 value 93.366802
iter 20 value 85.526957
iter 30 value 85.526300
final value 85.526285
converged
Fitting Repeat 1
# weights: 103
initial value 97.025373
iter 10 value 94.269835
iter 20 value 86.477279
iter 30 value 85.663667
iter 40 value 84.890366
iter 50 value 84.675203
iter 60 value 84.420463
iter 70 value 84.402553
final value 84.401593
converged
Fitting Repeat 2
# weights: 103
initial value 107.494525
iter 10 value 94.432955
iter 20 value 90.290042
iter 30 value 89.531783
iter 40 value 87.496074
iter 50 value 86.872046
iter 60 value 86.700584
iter 70 value 84.881770
iter 80 value 84.836240
iter 90 value 84.820702
iter 100 value 84.406500
final value 84.406500
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 98.693049
iter 10 value 95.193115
iter 20 value 94.506720
iter 30 value 94.482412
iter 40 value 89.978056
iter 50 value 86.983561
iter 60 value 85.946168
iter 70 value 85.460308
iter 80 value 84.754540
iter 90 value 84.405653
iter 100 value 84.401644
final value 84.401644
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.354575
iter 10 value 94.386859
iter 20 value 89.234921
iter 30 value 85.150739
iter 40 value 84.675481
iter 50 value 83.513695
iter 60 value 81.271105
iter 70 value 80.637052
iter 80 value 80.597662
iter 90 value 80.592046
iter 100 value 80.576959
final value 80.576959
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 96.793093
iter 10 value 94.498013
iter 20 value 93.597572
iter 30 value 87.790249
iter 40 value 83.852108
iter 50 value 83.372212
iter 60 value 83.361830
iter 70 value 83.192551
iter 80 value 82.960235
final value 82.953276
converged
Fitting Repeat 1
# weights: 305
initial value 107.480709
iter 10 value 94.477463
iter 20 value 93.888788
iter 30 value 85.657314
iter 40 value 84.922310
iter 50 value 84.712594
iter 60 value 84.274947
iter 70 value 84.206488
iter 80 value 83.877427
iter 90 value 81.061615
iter 100 value 80.664540
final value 80.664540
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.783198
iter 10 value 94.461216
iter 20 value 91.861694
iter 30 value 86.057586
iter 40 value 84.467687
iter 50 value 83.321595
iter 60 value 82.506584
iter 70 value 82.247695
iter 80 value 80.659345
iter 90 value 79.899946
iter 100 value 79.273262
final value 79.273262
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.749319
iter 10 value 94.470229
iter 20 value 89.085687
iter 30 value 85.525388
iter 40 value 84.650824
iter 50 value 82.180929
iter 60 value 80.549857
iter 70 value 80.311080
iter 80 value 79.684072
iter 90 value 79.648075
iter 100 value 79.591669
final value 79.591669
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.393499
iter 10 value 94.750373
iter 20 value 91.819561
iter 30 value 84.793135
iter 40 value 84.570147
iter 50 value 83.604060
iter 60 value 81.352825
iter 70 value 80.684848
iter 80 value 80.518965
iter 90 value 80.351713
iter 100 value 79.704777
final value 79.704777
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 112.796301
iter 10 value 94.734016
iter 20 value 94.300169
iter 30 value 90.357756
iter 40 value 85.731165
iter 50 value 85.156656
iter 60 value 84.063435
iter 70 value 80.541314
iter 80 value 79.969922
iter 90 value 79.601050
iter 100 value 79.332553
final value 79.332553
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.774824
iter 10 value 94.390553
iter 20 value 90.365917
iter 30 value 84.200601
iter 40 value 81.285167
iter 50 value 80.827755
iter 60 value 79.675196
iter 70 value 79.432257
iter 80 value 79.288050
iter 90 value 79.100782
iter 100 value 79.058858
final value 79.058858
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.907269
iter 10 value 94.015170
iter 20 value 87.680071
iter 30 value 85.344810
iter 40 value 84.626059
iter 50 value 84.448568
iter 60 value 84.115616
iter 70 value 83.429476
iter 80 value 81.801822
iter 90 value 79.402534
iter 100 value 79.222502
final value 79.222502
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 121.011356
iter 10 value 94.643513
iter 20 value 91.083521
iter 30 value 86.464064
iter 40 value 84.548352
iter 50 value 82.849475
iter 60 value 80.162131
iter 70 value 79.609825
iter 80 value 79.451102
iter 90 value 79.058830
iter 100 value 78.856754
final value 78.856754
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 117.524107
iter 10 value 96.197426
iter 20 value 94.477146
iter 30 value 93.484889
iter 40 value 91.632047
iter 50 value 85.592072
iter 60 value 85.220590
iter 70 value 83.671820
iter 80 value 81.403571
iter 90 value 81.124187
iter 100 value 80.069235
final value 80.069235
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 116.940737
iter 10 value 94.253172
iter 20 value 87.668218
iter 30 value 84.742502
iter 40 value 83.656011
iter 50 value 82.386564
iter 60 value 81.757597
iter 70 value 81.316594
iter 80 value 81.047562
iter 90 value 80.967068
iter 100 value 80.835753
final value 80.835753
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.454544
final value 94.485802
converged
Fitting Repeat 2
# weights: 103
initial value 99.774177
final value 94.485667
converged
Fitting Repeat 3
# weights: 103
initial value 97.040083
final value 94.486080
converged
Fitting Repeat 4
# weights: 103
initial value 97.448018
final value 93.703647
converged
Fitting Repeat 5
# weights: 103
initial value 94.345095
iter 10 value 93.676349
iter 20 value 93.675478
iter 30 value 90.219350
iter 40 value 89.857340
iter 50 value 86.820038
iter 60 value 84.460634
iter 70 value 84.026924
iter 80 value 83.926247
iter 90 value 83.869079
final value 83.868935
converged
Fitting Repeat 1
# weights: 305
initial value 95.721209
iter 10 value 93.760775
iter 20 value 93.706821
iter 30 value 93.636534
final value 93.431371
converged
Fitting Repeat 2
# weights: 305
initial value 106.137339
iter 10 value 94.488807
iter 20 value 94.160301
iter 30 value 93.683090
iter 40 value 93.181011
iter 50 value 91.118809
iter 60 value 91.012437
iter 70 value 90.940668
iter 80 value 90.907414
iter 90 value 90.794181
iter 100 value 90.780738
final value 90.780738
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.456478
iter 10 value 94.488844
iter 20 value 94.382046
iter 30 value 92.724493
iter 40 value 92.616596
iter 50 value 92.615354
iter 60 value 92.615103
final value 92.615094
converged
Fitting Repeat 4
# weights: 305
initial value 95.685430
iter 10 value 94.483656
iter 20 value 93.717772
iter 30 value 93.501929
final value 93.501910
converged
Fitting Repeat 5
# weights: 305
initial value 96.003942
iter 10 value 94.489107
iter 20 value 94.471614
iter 30 value 85.714904
iter 40 value 85.026095
iter 50 value 84.777002
iter 60 value 84.633896
iter 70 value 83.663936
iter 80 value 80.779875
iter 90 value 78.694129
iter 100 value 77.851121
final value 77.851121
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 124.650364
iter 10 value 94.515467
iter 20 value 94.481788
iter 30 value 94.185688
iter 40 value 93.526206
iter 50 value 83.410118
iter 60 value 82.712394
iter 70 value 82.433338
iter 80 value 82.309584
iter 90 value 82.278912
iter 100 value 82.266784
final value 82.266784
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 112.806609
iter 10 value 94.492017
iter 20 value 94.484403
iter 30 value 87.482612
iter 40 value 85.946523
iter 50 value 84.180479
iter 60 value 84.127743
iter 70 value 84.126409
iter 80 value 84.120440
iter 90 value 84.120165
iter 100 value 83.221806
final value 83.221806
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.443770
iter 10 value 91.969632
iter 20 value 84.730697
iter 30 value 84.631396
iter 40 value 84.577100
iter 50 value 84.571356
iter 60 value 84.027547
iter 70 value 83.823448
iter 80 value 83.785998
iter 90 value 83.349460
iter 100 value 83.088713
final value 83.088713
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 98.920732
iter 10 value 94.475457
iter 20 value 93.553533
iter 30 value 84.980445
iter 40 value 84.537245
iter 50 value 84.535702
iter 60 value 84.532199
iter 70 value 83.346134
iter 80 value 82.855988
iter 90 value 82.355190
iter 100 value 80.456797
final value 80.456797
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 97.263177
iter 10 value 93.872822
iter 20 value 93.679912
iter 30 value 93.644758
iter 40 value 93.135976
iter 50 value 92.231494
iter 60 value 92.226997
iter 70 value 92.189543
iter 80 value 92.167544
iter 90 value 91.614745
iter 100 value 90.829360
final value 90.829360
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 107.266033
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 95.935031
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 98.389223
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 102.088947
iter 10 value 92.945395
final value 92.945355
converged
Fitting Repeat 5
# weights: 103
initial value 97.198448
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 103.138462
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 106.457272
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 97.972641
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 95.313236
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 95.258238
final value 93.810010
converged
Fitting Repeat 1
# weights: 507
initial value 106.950908
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 111.844715
iter 10 value 94.052910
iter 10 value 94.052910
iter 10 value 94.052910
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 123.281413
iter 10 value 92.945355
iter 10 value 92.945355
iter 10 value 92.945355
final value 92.945355
converged
Fitting Repeat 4
# weights: 507
initial value 96.823014
iter 10 value 87.183237
iter 20 value 86.484957
iter 30 value 86.256280
iter 40 value 86.252837
final value 86.252784
converged
Fitting Repeat 5
# weights: 507
initial value 96.082863
iter 10 value 89.951712
iter 20 value 87.159187
iter 20 value 87.159187
iter 20 value 87.159187
final value 87.159187
converged
Fitting Repeat 1
# weights: 103
initial value 95.695071
iter 10 value 92.841831
iter 20 value 92.687404
iter 30 value 91.888044
iter 40 value 90.173695
iter 50 value 88.201774
iter 60 value 84.184935
iter 70 value 83.653445
iter 80 value 83.262480
iter 90 value 83.183225
iter 100 value 83.093926
final value 83.093926
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 107.086801
iter 10 value 94.056600
iter 20 value 93.263076
iter 30 value 87.309001
iter 40 value 86.640779
iter 50 value 83.957719
iter 60 value 82.417776
iter 70 value 82.185622
iter 80 value 82.048546
iter 90 value 82.033188
iter 100 value 82.026139
final value 82.026139
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 100.218774
iter 10 value 92.971775
iter 20 value 91.902021
iter 30 value 85.421290
iter 40 value 85.027428
iter 50 value 84.902397
iter 60 value 83.289899
iter 70 value 82.535367
iter 80 value 82.103189
iter 90 value 82.036090
final value 82.026137
converged
Fitting Repeat 4
# weights: 103
initial value 99.551383
iter 10 value 94.061041
iter 20 value 94.025021
iter 30 value 93.353412
iter 40 value 93.247914
iter 50 value 93.238123
iter 60 value 92.938623
iter 70 value 87.504907
iter 80 value 84.202127
iter 90 value 83.511198
iter 100 value 82.837753
final value 82.837753
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 105.203612
iter 10 value 93.482072
iter 20 value 86.723452
iter 30 value 85.274822
iter 40 value 85.156055
final value 85.154214
converged
Fitting Repeat 1
# weights: 305
initial value 102.975628
iter 10 value 94.057412
iter 20 value 93.543238
iter 30 value 89.110787
iter 40 value 87.328543
iter 50 value 83.466447
iter 60 value 82.486193
iter 70 value 81.949750
iter 80 value 81.615628
iter 90 value 81.280762
iter 100 value 81.230381
final value 81.230381
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 121.740611
iter 10 value 94.058121
iter 20 value 88.096757
iter 30 value 86.657000
iter 40 value 86.155349
iter 50 value 84.977684
iter 60 value 83.356570
iter 70 value 82.261274
iter 80 value 82.175855
iter 90 value 82.157399
iter 100 value 82.084535
final value 82.084535
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.643029
iter 10 value 93.931382
iter 20 value 93.503585
iter 30 value 89.957980
iter 40 value 88.623796
iter 50 value 83.792519
iter 60 value 82.907422
iter 70 value 82.153229
iter 80 value 81.110787
iter 90 value 80.861471
iter 100 value 80.839303
final value 80.839303
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 112.466555
iter 10 value 96.530437
iter 20 value 90.113980
iter 30 value 88.231533
iter 40 value 85.487638
iter 50 value 82.885830
iter 60 value 81.583535
iter 70 value 81.149791
iter 80 value 81.088291
iter 90 value 81.037429
iter 100 value 80.950002
final value 80.950002
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.598601
iter 10 value 93.449610
iter 20 value 92.789794
iter 30 value 92.683307
iter 40 value 88.491585
iter 50 value 84.179154
iter 60 value 82.670858
iter 70 value 81.463149
iter 80 value 81.241404
iter 90 value 81.181546
iter 100 value 81.140391
final value 81.140391
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 110.484473
iter 10 value 94.120385
iter 20 value 91.889145
iter 30 value 87.853674
iter 40 value 85.956732
iter 50 value 84.340675
iter 60 value 83.965592
iter 70 value 82.101498
iter 80 value 81.285035
iter 90 value 80.883598
iter 100 value 80.851206
final value 80.851206
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 119.896747
iter 10 value 94.003905
iter 20 value 92.738813
iter 30 value 88.649886
iter 40 value 85.776022
iter 50 value 85.609017
iter 60 value 85.253790
iter 70 value 83.578856
iter 80 value 82.013414
iter 90 value 81.211267
iter 100 value 80.819812
final value 80.819812
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 122.375252
iter 10 value 93.009244
iter 20 value 92.762921
iter 30 value 91.349832
iter 40 value 88.020516
iter 50 value 85.313298
iter 60 value 84.785592
iter 70 value 83.534009
iter 80 value 81.625504
iter 90 value 80.957036
iter 100 value 80.577770
final value 80.577770
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.447964
iter 10 value 96.058111
iter 20 value 88.644768
iter 30 value 86.632224
iter 40 value 84.255775
iter 50 value 82.354944
iter 60 value 81.054395
iter 70 value 80.789608
iter 80 value 80.617507
iter 90 value 80.574310
iter 100 value 80.410332
final value 80.410332
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.206998
iter 10 value 94.127052
iter 20 value 93.631410
iter 30 value 89.807703
iter 40 value 89.555496
iter 50 value 85.695371
iter 60 value 83.718559
iter 70 value 83.196069
iter 80 value 82.841950
iter 90 value 82.224604
iter 100 value 81.719987
final value 81.719987
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 107.265111
final value 94.054803
converged
Fitting Repeat 2
# weights: 103
initial value 95.188628
final value 94.054835
converged
Fitting Repeat 3
# weights: 103
initial value 101.229080
final value 94.054397
converged
Fitting Repeat 4
# weights: 103
initial value 101.291823
final value 94.054400
converged
Fitting Repeat 5
# weights: 103
initial value 95.362908
final value 94.054549
converged
Fitting Repeat 1
# weights: 305
initial value 101.179442
iter 10 value 94.057505
iter 20 value 94.053220
iter 20 value 94.053220
iter 20 value 94.053219
final value 94.053219
converged
Fitting Repeat 2
# weights: 305
initial value 95.817659
iter 10 value 94.054509
iter 20 value 94.035303
iter 30 value 92.735921
iter 40 value 92.001923
iter 50 value 85.441432
iter 60 value 84.503480
iter 70 value 83.717747
iter 80 value 83.713091
final value 83.711778
converged
Fitting Repeat 3
# weights: 305
initial value 96.981145
iter 10 value 94.058250
iter 20 value 94.015762
iter 30 value 92.945866
iter 30 value 92.945866
iter 30 value 92.945866
final value 92.945866
converged
Fitting Repeat 4
# weights: 305
initial value 104.808278
iter 10 value 92.798688
iter 20 value 92.700540
iter 30 value 92.695886
iter 40 value 88.506088
iter 50 value 83.783930
iter 60 value 83.707418
iter 70 value 83.660111
final value 83.660104
converged
Fitting Repeat 5
# weights: 305
initial value 95.475704
iter 10 value 93.762918
iter 20 value 93.677006
iter 30 value 92.528338
iter 40 value 89.426224
iter 50 value 89.405960
iter 60 value 89.219739
iter 70 value 87.972086
iter 80 value 87.832250
iter 90 value 87.830089
iter 100 value 87.829998
final value 87.829998
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 113.533755
iter 10 value 94.061258
iter 20 value 93.673278
iter 30 value 92.480027
iter 40 value 91.485659
iter 50 value 91.432897
iter 60 value 91.412616
iter 70 value 91.411883
iter 80 value 91.411484
final value 91.411255
converged
Fitting Repeat 2
# weights: 507
initial value 129.214566
iter 10 value 94.062035
iter 20 value 87.590067
iter 30 value 84.315143
iter 40 value 82.481535
iter 50 value 81.121160
iter 60 value 80.557865
iter 70 value 80.543302
iter 80 value 80.470348
iter 90 value 79.953990
iter 100 value 79.816888
final value 79.816888
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.286728
iter 10 value 92.954749
iter 20 value 92.948438
iter 30 value 89.753877
iter 40 value 84.472863
iter 50 value 84.465164
iter 60 value 84.458628
iter 70 value 83.792146
iter 80 value 82.125606
iter 90 value 80.938032
iter 100 value 80.038577
final value 80.038577
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 117.497542
iter 10 value 92.962267
iter 20 value 92.595806
iter 30 value 92.508548
iter 40 value 92.505686
iter 50 value 92.504953
final value 92.504871
converged
Fitting Repeat 5
# weights: 507
initial value 109.515459
iter 10 value 92.661294
iter 20 value 92.652769
iter 30 value 92.342244
iter 40 value 91.346946
iter 50 value 82.763703
iter 60 value 82.287966
iter 70 value 81.880324
iter 80 value 81.560048
iter 90 value 81.558703
final value 81.558362
converged
Fitting Repeat 1
# weights: 103
initial value 112.881990
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 99.753819
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 96.885692
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 102.712934
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 95.219431
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 97.453454
final value 93.836066
converged
Fitting Repeat 2
# weights: 305
initial value 101.549216
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 96.360849
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 95.505096
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 101.940894
iter 10 value 93.836217
final value 93.836066
converged
Fitting Repeat 1
# weights: 507
initial value 110.276745
iter 10 value 93.859787
final value 93.836066
converged
Fitting Repeat 2
# weights: 507
initial value 96.030048
final value 94.052448
converged
Fitting Repeat 3
# weights: 507
initial value 95.033061
iter 10 value 93.836066
iter 10 value 93.836066
iter 10 value 93.836066
final value 93.836066
converged
Fitting Repeat 4
# weights: 507
initial value 94.584266
final value 92.176403
converged
Fitting Repeat 5
# weights: 507
initial value 102.793898
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 98.599708
iter 10 value 94.064559
iter 20 value 93.951527
iter 30 value 93.885169
iter 40 value 88.014518
iter 50 value 86.153020
iter 60 value 85.699890
iter 70 value 82.569064
iter 80 value 82.543671
iter 90 value 82.539888
iter 100 value 82.539407
final value 82.539407
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 104.555341
iter 10 value 93.905668
iter 20 value 93.353936
iter 30 value 91.742413
iter 40 value 91.488491
iter 50 value 91.385666
iter 60 value 91.259434
final value 91.259230
converged
Fitting Repeat 3
# weights: 103
initial value 99.101776
iter 10 value 93.975115
iter 20 value 93.891063
iter 30 value 93.888957
iter 40 value 89.222294
iter 50 value 86.405235
iter 60 value 86.178040
iter 70 value 84.576450
iter 80 value 84.158805
iter 90 value 84.015584
iter 100 value 83.988412
final value 83.988412
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.947287
iter 10 value 94.110971
iter 20 value 94.055329
iter 30 value 92.357624
iter 40 value 86.971074
iter 50 value 84.646493
iter 60 value 82.167823
iter 70 value 81.768970
iter 80 value 81.641270
iter 90 value 81.628724
iter 100 value 81.616171
final value 81.616171
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 107.862128
iter 10 value 93.993052
iter 20 value 88.708521
iter 30 value 86.334514
iter 40 value 84.920297
iter 50 value 84.715052
iter 60 value 84.391682
iter 70 value 84.228063
iter 80 value 84.139149
iter 90 value 84.111210
iter 90 value 84.111210
final value 84.111210
converged
Fitting Repeat 1
# weights: 305
initial value 112.539936
iter 10 value 93.246231
iter 20 value 90.811317
iter 30 value 84.105776
iter 40 value 83.400163
iter 50 value 83.019996
iter 60 value 82.411762
iter 70 value 81.475866
iter 80 value 81.374363
iter 90 value 81.151160
iter 100 value 80.602588
final value 80.602588
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 109.888321
iter 10 value 94.506602
iter 20 value 91.639614
iter 30 value 89.321278
iter 40 value 87.413353
iter 50 value 83.930779
iter 60 value 83.698888
iter 70 value 83.364681
iter 80 value 82.395063
iter 90 value 82.122920
iter 100 value 82.095978
final value 82.095978
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 111.612473
iter 10 value 94.010781
iter 20 value 86.519086
iter 30 value 85.016122
iter 40 value 84.522438
iter 50 value 83.052744
iter 60 value 82.169109
iter 70 value 81.247140
iter 80 value 80.688920
iter 90 value 80.508808
iter 100 value 80.440304
final value 80.440304
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.331343
iter 10 value 95.816764
iter 20 value 87.423430
iter 30 value 85.227804
iter 40 value 84.486198
iter 50 value 83.041428
iter 60 value 81.079985
iter 70 value 80.778859
iter 80 value 80.591740
iter 90 value 80.369736
iter 100 value 80.273987
final value 80.273987
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.648906
iter 10 value 93.892741
iter 20 value 90.523294
iter 30 value 88.555378
iter 40 value 85.809799
iter 50 value 83.879515
iter 60 value 82.422991
iter 70 value 81.848570
iter 80 value 81.184507
iter 90 value 81.040646
iter 100 value 81.008571
final value 81.008571
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.499969
iter 10 value 93.996877
iter 20 value 88.424729
iter 30 value 86.222659
iter 40 value 85.164218
iter 50 value 83.668514
iter 60 value 83.098096
iter 70 value 81.639681
iter 80 value 80.374511
iter 90 value 80.187836
iter 100 value 79.986516
final value 79.986516
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 130.139701
iter 10 value 94.282164
iter 20 value 93.720265
iter 30 value 89.624047
iter 40 value 86.227954
iter 50 value 82.324490
iter 60 value 81.028901
iter 70 value 80.782011
iter 80 value 80.031366
iter 90 value 79.929321
iter 100 value 79.904029
final value 79.904029
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.654578
iter 10 value 90.834753
iter 20 value 85.386862
iter 30 value 83.943763
iter 40 value 83.615403
iter 50 value 83.190888
iter 60 value 82.358803
iter 70 value 81.193512
iter 80 value 80.624815
iter 90 value 80.535997
iter 100 value 80.135553
final value 80.135553
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.152068
iter 10 value 94.072663
iter 20 value 85.459913
iter 30 value 82.239572
iter 40 value 81.215573
iter 50 value 81.003659
iter 60 value 80.932609
iter 70 value 80.855321
iter 80 value 80.590372
iter 90 value 80.247203
iter 100 value 79.930725
final value 79.930725
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.850011
iter 10 value 92.295818
iter 20 value 85.621735
iter 30 value 84.295636
iter 40 value 82.754075
iter 50 value 82.151220
iter 60 value 81.363711
iter 70 value 80.951361
iter 80 value 80.339279
iter 90 value 80.143768
iter 100 value 80.068911
final value 80.068911
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.858103
final value 94.054510
converged
Fitting Repeat 2
# weights: 103
initial value 99.305702
final value 94.054764
converged
Fitting Repeat 3
# weights: 103
initial value 94.444714
iter 10 value 89.989785
iter 20 value 89.726090
iter 30 value 89.651214
final value 89.651194
converged
Fitting Repeat 4
# weights: 103
initial value 97.800837
iter 10 value 94.054819
final value 94.052914
converged
Fitting Repeat 5
# weights: 103
initial value 94.676409
final value 94.054762
converged
Fitting Repeat 1
# weights: 305
initial value 103.271485
iter 10 value 94.058136
iter 20 value 94.052941
iter 30 value 91.301748
iter 40 value 87.710549
iter 50 value 86.796976
iter 60 value 86.792722
final value 86.792714
converged
Fitting Repeat 2
# weights: 305
initial value 94.710929
iter 10 value 92.489066
iter 20 value 91.338407
iter 30 value 91.308070
iter 40 value 91.251051
iter 50 value 91.213404
final value 91.213271
converged
Fitting Repeat 3
# weights: 305
initial value 96.445424
iter 10 value 87.057463
iter 20 value 86.924854
iter 30 value 86.919814
iter 40 value 86.426637
iter 50 value 83.275498
iter 60 value 81.165663
iter 70 value 80.423862
iter 80 value 80.404111
iter 80 value 80.404111
final value 80.404111
converged
Fitting Repeat 4
# weights: 305
initial value 95.352666
iter 10 value 93.816853
iter 20 value 93.791252
iter 30 value 93.788181
iter 40 value 83.507216
iter 50 value 82.881770
iter 60 value 81.696806
iter 70 value 80.962855
final value 80.961946
converged
Fitting Repeat 5
# weights: 305
initial value 96.712156
iter 10 value 93.841283
iter 20 value 93.837819
iter 30 value 93.816601
iter 40 value 91.921722
iter 50 value 91.786862
final value 91.786856
converged
Fitting Repeat 1
# weights: 507
initial value 108.308949
iter 10 value 93.802770
iter 20 value 93.793789
iter 30 value 93.784208
final value 93.783247
converged
Fitting Repeat 2
# weights: 507
initial value 100.004395
iter 10 value 93.843992
iter 20 value 93.783053
iter 30 value 91.853795
iter 40 value 91.847803
iter 50 value 85.483609
iter 60 value 85.279491
iter 70 value 85.275441
iter 80 value 84.806007
iter 90 value 82.832637
iter 100 value 80.519340
final value 80.519340
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 102.527394
iter 10 value 94.060504
iter 20 value 92.285980
iter 30 value 83.874774
final value 83.873426
converged
Fitting Repeat 4
# weights: 507
initial value 109.765385
iter 10 value 94.061165
iter 20 value 93.481984
iter 30 value 89.087181
iter 40 value 89.053428
iter 50 value 89.053306
iter 60 value 87.245697
iter 70 value 84.414159
iter 80 value 84.170241
iter 90 value 84.016347
final value 84.015828
converged
Fitting Repeat 5
# weights: 507
initial value 96.811615
iter 10 value 93.844758
iter 20 value 93.839174
iter 30 value 93.819703
iter 40 value 93.818113
iter 50 value 93.773309
iter 60 value 93.763919
iter 70 value 93.759515
iter 80 value 93.758741
iter 90 value 84.767645
iter 100 value 83.872314
final value 83.872314
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.957650
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 101.691123
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 96.610862
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 98.825630
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.392938
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 100.459282
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 112.995809
final value 94.354396
converged
Fitting Repeat 3
# weights: 305
initial value 105.334203
final value 94.354396
converged
Fitting Repeat 4
# weights: 305
initial value 99.294127
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 106.828828
iter 10 value 94.356196
final value 94.354396
converged
Fitting Repeat 1
# weights: 507
initial value 123.288635
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 101.904844
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 96.753771
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 121.823734
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 107.669966
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 102.604949
iter 10 value 94.462449
iter 20 value 94.289247
iter 30 value 92.677111
iter 40 value 92.024051
iter 50 value 91.404070
iter 60 value 90.759234
iter 70 value 90.705532
final value 90.704902
converged
Fitting Repeat 2
# weights: 103
initial value 99.615491
iter 10 value 93.320295
iter 20 value 88.542168
iter 30 value 86.144362
iter 40 value 83.432197
iter 50 value 82.556110
iter 60 value 82.325626
iter 70 value 82.253369
iter 80 value 82.214997
final value 82.212106
converged
Fitting Repeat 3
# weights: 103
initial value 102.496400
iter 10 value 94.486859
iter 20 value 94.406517
iter 30 value 89.896067
iter 40 value 87.768751
iter 50 value 87.102239
iter 60 value 85.865187
iter 70 value 85.207203
iter 80 value 85.075100
iter 90 value 85.007009
final value 85.004610
converged
Fitting Repeat 4
# weights: 103
initial value 106.834558
iter 10 value 94.482414
iter 20 value 93.317329
iter 30 value 92.284505
iter 40 value 92.268141
iter 50 value 91.250527
iter 60 value 85.107740
iter 70 value 83.928425
iter 80 value 83.510740
iter 90 value 83.342721
iter 100 value 82.928834
final value 82.928834
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 98.134816
iter 10 value 94.486640
iter 20 value 94.374834
iter 30 value 90.362468
iter 40 value 89.214480
iter 50 value 87.175940
iter 60 value 85.259850
iter 70 value 85.018459
iter 80 value 84.883533
iter 90 value 84.821740
iter 100 value 84.810177
final value 84.810177
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 109.722814
iter 10 value 95.153267
iter 20 value 94.386283
iter 30 value 89.915259
iter 40 value 88.032828
iter 50 value 87.288847
iter 60 value 86.901704
iter 70 value 85.294911
iter 80 value 84.401473
iter 90 value 83.249478
iter 100 value 83.164273
final value 83.164273
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.412522
iter 10 value 94.576747
iter 20 value 94.391758
iter 30 value 90.074756
iter 40 value 86.423847
iter 50 value 85.738686
iter 60 value 83.177475
iter 70 value 82.826229
iter 80 value 82.670360
iter 90 value 82.449256
iter 100 value 82.131500
final value 82.131500
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 122.861115
iter 10 value 94.487645
iter 20 value 94.373984
iter 30 value 86.735955
iter 40 value 86.349475
iter 50 value 84.864987
iter 60 value 83.694309
iter 70 value 83.180066
iter 80 value 82.867758
iter 90 value 82.527622
iter 100 value 81.717463
final value 81.717463
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.953704
iter 10 value 94.587276
iter 20 value 94.491641
iter 30 value 89.600667
iter 40 value 85.580624
iter 50 value 83.761367
iter 60 value 83.442995
iter 70 value 82.808200
iter 80 value 82.291248
iter 90 value 81.883957
iter 100 value 81.808936
final value 81.808936
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.809903
iter 10 value 94.620677
iter 20 value 94.473088
iter 30 value 94.287811
iter 40 value 89.373635
iter 50 value 88.329172
iter 60 value 87.540952
iter 70 value 86.694945
iter 80 value 85.120106
iter 90 value 84.255937
iter 100 value 83.369547
final value 83.369547
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.564527
iter 10 value 87.295568
iter 20 value 86.209170
iter 30 value 84.741844
iter 40 value 82.113717
iter 50 value 81.694991
iter 60 value 81.301286
iter 70 value 81.049107
iter 80 value 80.945887
iter 90 value 80.862913
iter 100 value 80.813391
final value 80.813391
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 121.051378
iter 10 value 100.332487
iter 20 value 94.841252
iter 30 value 94.496690
iter 40 value 86.399491
iter 50 value 85.338612
iter 60 value 84.841007
iter 70 value 84.708090
iter 80 value 84.293375
iter 90 value 82.911726
iter 100 value 82.278464
final value 82.278464
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.204691
iter 10 value 94.461323
iter 20 value 89.156561
iter 30 value 87.229566
iter 40 value 86.335845
iter 50 value 84.160665
iter 60 value 83.202739
iter 70 value 82.990209
iter 80 value 82.271974
iter 90 value 81.839024
iter 100 value 81.666727
final value 81.666727
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.418007
iter 10 value 95.145996
iter 20 value 93.772325
iter 30 value 92.219374
iter 40 value 89.766179
iter 50 value 85.978024
iter 60 value 82.716955
iter 70 value 81.792555
iter 80 value 81.233715
iter 90 value 81.055306
iter 100 value 80.886066
final value 80.886066
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.960804
iter 10 value 97.242736
iter 20 value 96.632561
iter 30 value 93.806677
iter 40 value 87.479213
iter 50 value 84.677832
iter 60 value 84.255678
iter 70 value 82.827303
iter 80 value 82.176287
iter 90 value 81.437655
iter 100 value 81.182281
final value 81.182281
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.001371
final value 94.485834
converged
Fitting Repeat 2
# weights: 103
initial value 97.192878
final value 94.485886
converged
Fitting Repeat 3
# weights: 103
initial value 97.889206
final value 94.485765
converged
Fitting Repeat 4
# weights: 103
initial value 98.270926
final value 94.485576
converged
Fitting Repeat 5
# weights: 103
initial value 96.506102
final value 94.485967
converged
Fitting Repeat 1
# weights: 305
initial value 97.161390
iter 10 value 93.441637
iter 20 value 86.736011
iter 30 value 86.469966
iter 40 value 85.339288
iter 50 value 85.278926
iter 60 value 85.259825
final value 85.259172
converged
Fitting Repeat 2
# weights: 305
initial value 95.099679
iter 10 value 94.488585
iter 20 value 94.433675
iter 30 value 88.876698
final value 88.556347
converged
Fitting Repeat 3
# weights: 305
initial value 106.178276
iter 10 value 94.488805
iter 20 value 94.482695
iter 30 value 88.516414
iter 40 value 86.972436
iter 50 value 86.968888
iter 60 value 86.953723
iter 70 value 86.953097
iter 80 value 86.934266
iter 90 value 83.341273
iter 100 value 83.291507
final value 83.291507
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.444346
iter 10 value 94.486937
iter 20 value 94.380701
iter 30 value 86.492626
iter 40 value 83.997706
iter 50 value 83.884182
iter 60 value 83.882046
iter 70 value 83.861168
iter 80 value 83.849630
iter 90 value 83.849516
iter 100 value 83.848832
final value 83.848832
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.052683
iter 10 value 94.489373
iter 20 value 94.470116
iter 30 value 94.311541
final value 94.308240
converged
Fitting Repeat 1
# weights: 507
initial value 136.729155
iter 10 value 94.492435
iter 20 value 94.430573
iter 30 value 92.357927
iter 40 value 92.093921
iter 50 value 92.051465
final value 92.051347
converged
Fitting Repeat 2
# weights: 507
initial value 100.921920
iter 10 value 94.490287
iter 20 value 94.188456
iter 30 value 92.439507
iter 40 value 84.659398
iter 50 value 83.026482
iter 60 value 82.882535
iter 70 value 82.864231
iter 80 value 82.793476
iter 90 value 81.929549
iter 100 value 81.750323
final value 81.750323
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 101.285379
iter 10 value 94.494085
iter 20 value 94.441541
iter 30 value 87.081061
iter 40 value 86.497367
iter 50 value 86.167231
iter 60 value 86.166324
final value 86.166161
converged
Fitting Repeat 4
# weights: 507
initial value 110.589664
iter 10 value 94.490092
iter 20 value 93.139505
iter 30 value 91.893247
iter 40 value 90.103329
iter 50 value 88.857268
iter 60 value 88.844754
final value 88.844443
converged
Fitting Repeat 5
# weights: 507
initial value 98.341425
iter 10 value 94.490887
iter 20 value 94.363415
final value 94.355225
converged
Fitting Repeat 1
# weights: 103
initial value 98.553370
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.834418
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.508810
final value 94.470284
converged
Fitting Repeat 4
# weights: 103
initial value 100.680088
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.307627
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 103.151124
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 101.809220
final value 94.484218
converged
Fitting Repeat 3
# weights: 305
initial value 101.100136
iter 10 value 94.263776
iter 20 value 94.251197
iter 30 value 91.456397
iter 40 value 87.810102
iter 50 value 87.809592
final value 87.809072
converged
Fitting Repeat 4
# weights: 305
initial value 97.116516
iter 10 value 94.414752
final value 94.414729
converged
Fitting Repeat 5
# weights: 305
initial value 107.333518
final value 94.428839
converged
Fitting Repeat 1
# weights: 507
initial value 97.098231
final value 94.467391
converged
Fitting Repeat 2
# weights: 507
initial value 100.085331
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 106.485450
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 100.456569
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 98.071436
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 98.228904
iter 10 value 85.124575
iter 20 value 84.662914
iter 30 value 81.913703
iter 40 value 81.683657
iter 50 value 81.580216
iter 60 value 81.494096
iter 70 value 81.468015
final value 81.467571
converged
Fitting Repeat 2
# weights: 103
initial value 100.825701
iter 10 value 94.703450
iter 20 value 94.488516
iter 30 value 84.895848
iter 40 value 84.153020
iter 50 value 83.205511
iter 60 value 82.246819
iter 70 value 81.609201
iter 80 value 81.538790
iter 90 value 81.530049
iter 90 value 81.530048
final value 81.530048
converged
Fitting Repeat 3
# weights: 103
initial value 101.011813
iter 10 value 94.431030
iter 20 value 90.880166
iter 30 value 89.920817
iter 40 value 89.910468
iter 50 value 86.328755
iter 60 value 83.839464
iter 70 value 83.428183
iter 80 value 83.382234
iter 90 value 82.487030
iter 100 value 81.885815
final value 81.885815
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.050347
iter 10 value 94.486922
iter 20 value 93.394269
iter 30 value 87.334948
iter 40 value 86.025559
iter 50 value 85.018840
iter 60 value 84.940020
iter 70 value 82.221462
iter 80 value 81.916174
iter 90 value 81.879210
iter 100 value 81.870960
final value 81.870960
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 98.005726
iter 10 value 94.460071
iter 20 value 84.940721
iter 30 value 84.233112
iter 40 value 82.265543
iter 50 value 81.898050
iter 60 value 81.875914
iter 70 value 81.867655
iter 70 value 81.867655
iter 70 value 81.867655
final value 81.867655
converged
Fitting Repeat 1
# weights: 305
initial value 102.309898
iter 10 value 94.394840
iter 20 value 93.494421
iter 30 value 84.968068
iter 40 value 81.208563
iter 50 value 80.899421
iter 60 value 80.218015
iter 70 value 79.997835
iter 80 value 79.857529
iter 90 value 79.775073
iter 100 value 79.650160
final value 79.650160
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.329790
iter 10 value 93.655077
iter 20 value 86.025227
iter 30 value 84.159431
iter 40 value 82.243623
iter 50 value 80.470954
iter 60 value 80.403552
iter 70 value 80.225518
iter 80 value 79.361448
iter 90 value 78.816554
iter 100 value 78.441506
final value 78.441506
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 108.143698
iter 10 value 95.157180
iter 20 value 92.638314
iter 30 value 84.820350
iter 40 value 81.461203
iter 50 value 80.424669
iter 60 value 80.136517
iter 70 value 79.829053
iter 80 value 79.706856
iter 90 value 79.583847
iter 100 value 79.545036
final value 79.545036
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.852037
iter 10 value 95.157155
iter 20 value 93.757581
iter 30 value 88.028230
iter 40 value 85.477396
iter 50 value 81.979454
iter 60 value 81.702314
iter 70 value 81.358929
iter 80 value 79.836565
iter 90 value 79.574848
iter 100 value 79.472128
final value 79.472128
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 113.582741
iter 10 value 94.458165
iter 20 value 94.040986
iter 30 value 92.705653
iter 40 value 85.717903
iter 50 value 83.795704
iter 60 value 83.412261
iter 70 value 82.576726
iter 80 value 80.310054
iter 90 value 79.808840
iter 100 value 79.233424
final value 79.233424
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.623064
iter 10 value 93.954572
iter 20 value 84.996757
iter 30 value 83.568600
iter 40 value 83.372347
iter 50 value 82.989427
iter 60 value 82.398497
iter 70 value 80.864086
iter 80 value 80.455040
iter 90 value 79.478840
iter 100 value 78.947682
final value 78.947682
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.430864
iter 10 value 94.758553
iter 20 value 91.124730
iter 30 value 81.943797
iter 40 value 80.901859
iter 50 value 80.506070
iter 60 value 79.666389
iter 70 value 79.195405
iter 80 value 78.992167
iter 90 value 78.573499
iter 100 value 78.471924
final value 78.471924
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.295274
iter 10 value 94.130916
iter 20 value 93.847402
iter 30 value 92.540551
iter 40 value 85.044123
iter 50 value 83.107444
iter 60 value 81.335996
iter 70 value 80.412433
iter 80 value 80.130235
iter 90 value 79.983650
iter 100 value 79.400790
final value 79.400790
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.141383
iter 10 value 94.505299
iter 20 value 93.273923
iter 30 value 89.218084
iter 40 value 86.911039
iter 50 value 81.497633
iter 60 value 79.268800
iter 70 value 79.204725
iter 80 value 79.153591
iter 90 value 78.941435
iter 100 value 78.568962
final value 78.568962
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.647965
iter 10 value 94.531345
iter 20 value 90.411389
iter 30 value 85.937822
iter 40 value 81.806802
iter 50 value 80.351683
iter 60 value 79.504850
iter 70 value 78.825449
iter 80 value 78.593806
iter 90 value 78.382775
iter 100 value 78.361930
final value 78.361930
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 106.345621
final value 94.485665
converged
Fitting Repeat 2
# weights: 103
initial value 102.927251
final value 94.485603
converged
Fitting Repeat 3
# weights: 103
initial value 95.842479
final value 94.485883
converged
Fitting Repeat 4
# weights: 103
initial value 99.251222
final value 94.486030
converged
Fitting Repeat 5
# weights: 103
initial value 108.282493
final value 94.485876
converged
Fitting Repeat 1
# weights: 305
initial value 111.174933
iter 10 value 92.234800
iter 20 value 92.231991
iter 30 value 83.737955
iter 40 value 83.615241
iter 40 value 83.615240
iter 40 value 83.615240
final value 83.615240
converged
Fitting Repeat 2
# weights: 305
initial value 96.079732
iter 10 value 94.433627
iter 20 value 94.429139
iter 30 value 94.411213
iter 40 value 85.519997
iter 50 value 83.794472
iter 60 value 81.340316
iter 70 value 80.548128
iter 80 value 80.513786
iter 90 value 80.513412
iter 100 value 79.977618
final value 79.977618
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 95.527069
iter 10 value 94.489204
iter 20 value 83.806276
iter 30 value 83.788467
iter 40 value 83.787152
iter 50 value 83.786592
iter 60 value 83.615859
iter 70 value 83.615054
iter 80 value 83.613681
iter 80 value 83.613681
final value 83.613681
converged
Fitting Repeat 4
# weights: 305
initial value 103.478826
iter 10 value 93.220752
iter 20 value 91.111533
iter 30 value 81.752240
iter 40 value 81.604793
iter 50 value 81.237581
iter 60 value 80.552627
iter 70 value 80.253882
iter 80 value 80.233156
iter 90 value 80.228597
iter 100 value 80.208686
final value 80.208686
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 97.527843
iter 10 value 94.448025
iter 20 value 94.447205
final value 94.447199
converged
Fitting Repeat 1
# weights: 507
initial value 103.745898
iter 10 value 87.615559
iter 20 value 84.486055
iter 30 value 84.479472
iter 40 value 84.475067
iter 50 value 84.201722
iter 60 value 83.216316
iter 70 value 83.209251
iter 80 value 83.207472
iter 90 value 83.200850
iter 100 value 83.177727
final value 83.177727
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.359241
iter 10 value 87.292783
iter 20 value 82.863121
iter 30 value 81.305167
iter 40 value 81.260945
iter 50 value 80.681196
iter 60 value 80.611276
iter 70 value 80.610318
iter 80 value 80.601718
iter 90 value 80.581116
iter 100 value 80.187405
final value 80.187405
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 98.771594
iter 10 value 92.345966
iter 20 value 91.199113
iter 30 value 91.191579
iter 40 value 91.187010
iter 50 value 91.186669
iter 60 value 91.186415
iter 70 value 91.185630
iter 80 value 91.184085
iter 90 value 85.501693
iter 100 value 83.277955
final value 83.277955
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.014795
iter 10 value 91.541489
iter 20 value 86.627435
iter 30 value 84.580846
iter 40 value 83.390992
iter 50 value 83.337701
iter 60 value 83.337354
iter 70 value 83.332085
iter 80 value 83.330391
final value 83.329958
converged
Fitting Repeat 5
# weights: 507
initial value 111.914461
iter 10 value 94.492545
iter 20 value 94.483693
iter 30 value 94.291689
iter 40 value 87.053938
iter 50 value 82.752731
iter 60 value 82.731571
iter 70 value 82.729965
iter 80 value 82.728715
iter 90 value 82.548199
iter 100 value 81.291797
final value 81.291797
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 121.043087
iter 10 value 117.895485
iter 20 value 117.890356
iter 30 value 117.612264
iter 40 value 114.573587
iter 50 value 110.239621
iter 60 value 107.658561
iter 70 value 107.588289
iter 80 value 107.472366
iter 90 value 105.588823
iter 100 value 104.008767
final value 104.008767
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 117.920367
iter 10 value 112.999222
iter 20 value 108.530782
iter 30 value 107.059150
iter 40 value 106.920980
iter 50 value 106.832779
iter 60 value 106.830094
iter 70 value 106.827697
iter 80 value 106.827553
final value 106.827506
converged
Fitting Repeat 3
# weights: 305
initial value 133.866855
iter 10 value 117.763689
iter 20 value 115.706771
iter 30 value 107.267337
iter 40 value 106.657479
final value 106.656187
converged
Fitting Repeat 4
# weights: 305
initial value 158.049981
iter 10 value 117.896278
iter 20 value 117.891821
iter 30 value 116.943827
final value 105.366379
converged
Fitting Repeat 5
# weights: 305
initial value 128.005789
iter 10 value 117.894928
iter 20 value 107.601324
iter 30 value 107.011164
iter 40 value 107.005350
iter 50 value 107.004646
iter 60 value 107.001664
final value 107.001057
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 -- Fri Apr 24 00:31:38 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
40.933 1.484 102.167
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.771 | 0.485 | 34.319 | |
| FreqInteractors | 0.425 | 0.023 | 0.448 | |
| calculateAAC | 0.032 | 0.001 | 0.033 | |
| calculateAutocor | 0.269 | 0.011 | 0.280 | |
| calculateCTDC | 0.071 | 0.000 | 0.071 | |
| calculateCTDD | 0.465 | 0.000 | 0.465 | |
| calculateCTDT | 0.131 | 0.000 | 0.131 | |
| calculateCTriad | 0.445 | 0.000 | 0.445 | |
| calculateDC | 0.085 | 0.000 | 0.085 | |
| calculateF | 0.313 | 0.000 | 0.313 | |
| calculateKSAAP | 0.093 | 0.001 | 0.094 | |
| calculateQD_Sm | 1.991 | 0.010 | 2.001 | |
| calculateTC | 1.445 | 0.026 | 1.471 | |
| calculateTC_Sm | 0.277 | 0.001 | 0.278 | |
| corr_plot | 34.281 | 0.370 | 34.690 | |
| enrichfindP | 0.516 | 0.042 | 9.648 | |
| enrichfind_hp | 0.043 | 0.002 | 1.860 | |
| enrichplot | 0.535 | 0.005 | 0.540 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.446 | 0.030 | 3.835 | |
| getHPI | 0.001 | 0.000 | 0.000 | |
| get_negativePPI | 0.001 | 0.000 | 0.001 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.001 | 0.000 | 0.002 | |
| plotPPI | 0.089 | 0.000 | 0.090 | |
| pred_ensembel | 13.085 | 0.385 | 12.224 | |
| var_imp | 34.483 | 0.534 | 35.095 | |