Matineh Rahmatbakhsh
| Snapshot Date: 2026-03-10 13:45 -0400 (Tue, 10 Mar 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 -0400 (Sun, 28 Dec 2025) |
| Back to Build/check report for BioC 3.22: simplified long |
|
This page was generated on 2026-03-11 11:57 -0400 (Wed, 11 Mar 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" | 4892 |
| 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: 2026-03-11 00:20:06 -0400 (Wed, 11 Mar 2026) |
| EndedAt: 2026-03-11 00:35:06 -0400 (Wed, 11 Mar 2026) |
| EllapsedTime: 900.0 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 34.749 0.533 35.301
FSmethod 33.774 0.424 34.235
var_imp 33.416 0.720 34.142
pred_ensembel 12.900 0.238 11.914
enrichfindP 0.508 0.043 11.573
* 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 96.556780
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 101.765769
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 102.845684
iter 10 value 93.918755
iter 20 value 93.816618
iter 30 value 93.810019
iter 40 value 93.798698
final value 93.785768
converged
Fitting Repeat 4
# weights: 103
initial value 97.484602
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 110.100001
final value 94.052911
converged
Fitting Repeat 1
# weights: 305
initial value 94.545652
final value 93.946237
converged
Fitting Repeat 2
# weights: 305
initial value 110.110462
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 95.744092
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 105.828698
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 99.139412
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 98.727196
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 112.983168
iter 10 value 93.946237
iter 10 value 93.946237
iter 10 value 93.946237
final value 93.946237
converged
Fitting Repeat 3
# weights: 507
initial value 99.352146
iter 10 value 93.946237
iter 10 value 93.946237
iter 10 value 93.946237
final value 93.946237
converged
Fitting Repeat 4
# weights: 507
initial value 98.420598
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 97.679467
final value 93.946237
converged
Fitting Repeat 1
# weights: 103
initial value 101.170444
iter 10 value 94.073516
iter 20 value 88.404520
iter 30 value 85.937637
iter 40 value 83.825893
iter 50 value 82.043240
iter 60 value 81.921653
iter 70 value 81.216856
final value 81.201258
converged
Fitting Repeat 2
# weights: 103
initial value 100.589541
iter 10 value 94.054971
iter 20 value 93.134854
iter 30 value 91.409003
iter 40 value 85.721287
iter 50 value 84.225537
iter 60 value 81.985635
iter 70 value 81.359940
iter 80 value 81.215865
iter 90 value 81.201284
final value 81.201258
converged
Fitting Repeat 3
# weights: 103
initial value 105.894037
iter 10 value 93.998767
iter 20 value 93.228402
iter 30 value 93.015742
iter 40 value 88.751946
iter 50 value 83.629933
iter 60 value 83.190868
iter 70 value 83.113925
iter 80 value 83.058740
iter 90 value 82.974437
iter 100 value 82.958943
final value 82.958943
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 103.380383
iter 10 value 94.057252
iter 20 value 83.731625
iter 30 value 82.739970
iter 40 value 82.041134
iter 50 value 81.473719
iter 60 value 81.201877
final value 81.201258
converged
Fitting Repeat 5
# weights: 103
initial value 96.111629
iter 10 value 94.055498
iter 20 value 93.214006
iter 30 value 93.079630
iter 40 value 93.071068
iter 50 value 93.067535
iter 60 value 92.089404
iter 70 value 88.329487
iter 80 value 82.952283
iter 90 value 81.365963
iter 100 value 78.750971
final value 78.750971
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 100.482707
iter 10 value 93.921690
iter 20 value 90.901737
iter 30 value 81.540919
iter 40 value 79.183671
iter 50 value 77.781840
iter 60 value 77.239945
iter 70 value 76.970823
iter 80 value 76.885791
iter 90 value 76.855459
iter 100 value 76.801938
final value 76.801938
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.080184
iter 10 value 91.638367
iter 20 value 85.153766
iter 30 value 83.857077
iter 40 value 82.136069
iter 50 value 80.805234
iter 60 value 80.082552
iter 70 value 79.608933
iter 80 value 78.318030
iter 90 value 77.728950
iter 100 value 77.366455
final value 77.366455
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 117.898334
iter 10 value 93.664730
iter 20 value 93.183864
iter 30 value 92.848585
iter 40 value 88.015918
iter 50 value 83.332891
iter 60 value 81.662723
iter 70 value 80.329595
iter 80 value 79.590148
iter 90 value 79.201340
iter 100 value 79.012361
final value 79.012361
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 105.979473
iter 10 value 93.931127
iter 20 value 89.265570
iter 30 value 80.360335
iter 40 value 78.434104
iter 50 value 78.043773
iter 60 value 77.798974
iter 70 value 77.563676
iter 80 value 77.329591
iter 90 value 76.915030
iter 100 value 76.592102
final value 76.592102
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.138837
iter 10 value 93.871917
iter 20 value 86.262946
iter 30 value 84.789093
iter 40 value 84.155689
iter 50 value 84.036969
iter 60 value 82.309769
iter 70 value 80.365517
iter 80 value 78.887271
iter 90 value 78.472543
iter 100 value 77.648844
final value 77.648844
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 114.264074
iter 10 value 93.254888
iter 20 value 84.129003
iter 30 value 83.344745
iter 40 value 81.402370
iter 50 value 80.604980
iter 60 value 79.219336
iter 70 value 78.311065
iter 80 value 77.404973
iter 90 value 76.839134
iter 100 value 76.650228
final value 76.650228
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.141435
iter 10 value 88.496315
iter 20 value 83.226458
iter 30 value 78.677818
iter 40 value 77.640226
iter 50 value 77.514156
iter 60 value 77.240154
iter 70 value 76.704173
iter 80 value 76.450370
iter 90 value 76.399849
iter 100 value 76.318920
final value 76.318920
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 115.461224
iter 10 value 93.323481
iter 20 value 92.899469
iter 30 value 85.839722
iter 40 value 82.913323
iter 50 value 79.578099
iter 60 value 78.069303
iter 70 value 77.741793
iter 80 value 77.235026
iter 90 value 76.993702
iter 100 value 76.742488
final value 76.742488
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.185984
iter 10 value 94.098056
iter 20 value 88.847269
iter 30 value 84.870494
iter 40 value 82.716183
iter 50 value 79.913149
iter 60 value 79.462081
iter 70 value 77.525244
iter 80 value 77.365065
iter 90 value 77.041713
iter 100 value 76.875590
final value 76.875590
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 116.648387
iter 10 value 93.578546
iter 20 value 93.216068
iter 30 value 89.452573
iter 40 value 84.161930
iter 50 value 80.082557
iter 60 value 77.924566
iter 70 value 76.958145
iter 80 value 76.648173
iter 90 value 76.549277
iter 100 value 76.372580
final value 76.372580
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.419446
iter 10 value 93.183588
iter 20 value 93.010269
iter 30 value 92.874681
iter 40 value 92.874252
iter 50 value 92.873268
final value 92.872871
converged
Fitting Repeat 2
# weights: 103
initial value 95.433079
final value 94.054383
converged
Fitting Repeat 3
# weights: 103
initial value 95.362724
final value 94.054931
converged
Fitting Repeat 4
# weights: 103
initial value 93.912836
final value 93.076115
converged
Fitting Repeat 5
# weights: 103
initial value 95.247932
iter 10 value 93.947696
iter 20 value 93.183895
iter 30 value 86.477610
iter 40 value 84.698555
iter 50 value 79.649708
iter 60 value 79.305993
iter 70 value 79.006113
iter 80 value 78.975160
iter 90 value 78.974828
iter 100 value 78.973123
final value 78.973123
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 100.348197
iter 10 value 92.959178
iter 20 value 92.957000
iter 30 value 90.192383
iter 40 value 90.076054
iter 50 value 89.811534
iter 60 value 89.665770
iter 70 value 89.663738
iter 80 value 89.443623
iter 90 value 89.258271
iter 100 value 89.067520
final value 89.067520
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 111.293988
iter 10 value 94.057120
iter 20 value 94.042447
iter 30 value 91.636990
iter 40 value 83.329113
iter 50 value 80.421514
iter 60 value 79.305517
iter 70 value 79.303185
iter 80 value 79.039350
iter 90 value 78.976413
final value 78.976406
converged
Fitting Repeat 3
# weights: 305
initial value 115.970904
iter 10 value 94.058257
iter 20 value 94.053330
iter 20 value 94.053330
iter 20 value 94.053330
final value 94.053330
converged
Fitting Repeat 4
# weights: 305
initial value 94.517922
iter 10 value 93.539675
iter 20 value 93.295711
iter 30 value 93.247557
iter 40 value 91.971148
iter 50 value 90.663861
iter 60 value 90.662339
iter 70 value 90.661525
iter 80 value 90.660716
iter 90 value 90.603888
final value 90.603530
converged
Fitting Repeat 5
# weights: 305
initial value 107.490399
iter 10 value 89.420448
iter 20 value 85.060217
iter 30 value 85.041933
iter 40 value 84.194303
iter 50 value 84.165247
final value 84.163538
converged
Fitting Repeat 1
# weights: 507
initial value 106.664899
iter 10 value 83.493814
iter 20 value 81.888540
iter 30 value 81.823719
iter 40 value 81.822908
iter 50 value 81.819351
final value 81.818317
converged
Fitting Repeat 2
# weights: 507
initial value 94.831660
iter 10 value 93.954279
iter 20 value 93.704012
iter 30 value 85.756979
iter 40 value 84.676072
iter 50 value 84.545885
iter 60 value 84.494525
iter 70 value 84.472476
iter 80 value 84.379087
iter 90 value 80.965006
iter 100 value 78.577483
final value 78.577483
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.982403
iter 10 value 93.912574
iter 20 value 93.440377
iter 30 value 85.863780
iter 40 value 82.891459
iter 50 value 82.793728
iter 60 value 82.793201
iter 70 value 82.791948
iter 80 value 82.031019
iter 90 value 79.493376
iter 100 value 79.226866
final value 79.226866
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 99.344484
iter 10 value 92.331607
iter 20 value 88.093852
iter 30 value 88.083362
iter 40 value 85.103106
iter 50 value 84.596852
iter 60 value 84.586601
iter 70 value 84.581294
final value 84.578521
converged
Fitting Repeat 5
# weights: 507
initial value 97.589377
iter 10 value 93.954400
iter 20 value 93.947126
iter 30 value 91.169451
iter 40 value 90.336732
iter 50 value 89.912981
iter 60 value 89.911688
iter 70 value 89.911425
iter 80 value 89.911017
iter 90 value 86.652717
iter 100 value 79.919153
final value 79.919153
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.201554
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 100.652254
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 107.036636
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.296283
iter 10 value 94.484213
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.127233
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 100.487187
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 100.992239
iter 10 value 94.163789
final value 93.974641
converged
Fitting Repeat 3
# weights: 305
initial value 99.089234
final value 94.026542
converged
Fitting Repeat 4
# weights: 305
initial value 97.938934
final value 94.026542
converged
Fitting Repeat 5
# weights: 305
initial value 94.762836
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 105.180799
final value 94.026542
converged
Fitting Repeat 2
# weights: 507
initial value 98.818795
iter 10 value 93.745455
final value 93.745298
converged
Fitting Repeat 3
# weights: 507
initial value 98.504811
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 105.925933
final value 94.026542
converged
Fitting Repeat 5
# weights: 507
initial value 100.243785
iter 10 value 93.999468
iter 20 value 93.821675
iter 30 value 93.820835
final value 93.820833
converged
Fitting Repeat 1
# weights: 103
initial value 100.253541
iter 10 value 94.313682
iter 20 value 93.872421
iter 30 value 92.879900
iter 40 value 88.272620
iter 50 value 88.023626
iter 60 value 87.917707
final value 87.917641
converged
Fitting Repeat 2
# weights: 103
initial value 97.436723
iter 10 value 94.260581
iter 20 value 92.866462
iter 30 value 89.699606
iter 40 value 89.111029
iter 50 value 87.543311
iter 60 value 87.092087
iter 70 value 86.646438
iter 80 value 85.719937
iter 90 value 85.566114
iter 100 value 85.552451
final value 85.552451
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 104.875124
iter 10 value 94.487431
iter 20 value 94.387439
iter 30 value 93.906907
iter 40 value 93.837853
iter 50 value 90.772817
iter 60 value 88.485016
iter 70 value 88.012039
iter 80 value 87.943209
iter 90 value 87.875188
iter 100 value 87.822965
final value 87.822965
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.881662
iter 10 value 94.245366
iter 20 value 89.987936
iter 30 value 88.949647
iter 40 value 88.609844
iter 50 value 88.000075
iter 60 value 87.897224
iter 70 value 87.390735
iter 80 value 86.474661
iter 90 value 85.684384
iter 100 value 85.544537
final value 85.544537
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 100.479790
iter 10 value 94.488291
iter 20 value 92.814629
iter 30 value 92.570763
iter 40 value 91.633676
iter 50 value 87.614164
iter 60 value 86.207309
iter 70 value 85.575687
iter 80 value 85.547040
iter 90 value 85.530156
final value 85.529800
converged
Fitting Repeat 1
# weights: 305
initial value 105.596437
iter 10 value 93.969038
iter 20 value 87.831564
iter 30 value 86.912113
iter 40 value 85.765137
iter 50 value 85.661013
iter 60 value 85.444531
iter 70 value 84.979918
iter 80 value 84.936020
iter 90 value 84.781265
iter 100 value 84.574665
final value 84.574665
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 131.819507
iter 10 value 94.501273
iter 20 value 93.906891
iter 30 value 93.514205
iter 40 value 91.170877
iter 50 value 88.297232
iter 60 value 87.317097
iter 70 value 86.385984
iter 80 value 85.152461
iter 90 value 84.867797
iter 100 value 84.734848
final value 84.734848
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.418415
iter 10 value 94.476353
iter 20 value 90.136923
iter 30 value 88.853208
iter 40 value 88.450347
iter 50 value 88.027936
iter 60 value 87.921334
iter 70 value 87.682999
iter 80 value 86.741017
iter 90 value 86.352503
iter 100 value 85.627219
final value 85.627219
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 119.092443
iter 10 value 93.579917
iter 20 value 89.197115
iter 30 value 86.072170
iter 40 value 85.163080
iter 50 value 85.102304
iter 60 value 84.963505
iter 70 value 84.711163
iter 80 value 84.431996
iter 90 value 84.294529
iter 100 value 84.212479
final value 84.212479
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 111.877298
iter 10 value 94.509819
iter 20 value 92.813417
iter 30 value 89.459474
iter 40 value 87.943052
iter 50 value 87.158771
iter 60 value 87.087718
iter 70 value 86.976615
iter 80 value 85.892120
iter 90 value 85.035396
iter 100 value 84.941907
final value 84.941907
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 115.410730
iter 10 value 94.500914
iter 20 value 91.827830
iter 30 value 87.384487
iter 40 value 86.097333
iter 50 value 85.146628
iter 60 value 85.004749
iter 70 value 84.795210
iter 80 value 84.343355
iter 90 value 84.286427
iter 100 value 84.074886
final value 84.074886
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.684371
iter 10 value 94.587724
iter 20 value 90.108842
iter 30 value 89.500161
iter 40 value 86.351559
iter 50 value 85.779244
iter 60 value 85.279785
iter 70 value 84.387879
iter 80 value 84.102335
iter 90 value 84.049683
iter 100 value 84.017475
final value 84.017475
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.264434
iter 10 value 94.473007
iter 20 value 93.993279
iter 30 value 88.418916
iter 40 value 87.128528
iter 50 value 86.047728
iter 60 value 85.133153
iter 70 value 84.758406
iter 80 value 84.375276
iter 90 value 84.242522
iter 100 value 84.010132
final value 84.010132
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 110.116134
iter 10 value 95.989474
iter 20 value 94.561203
iter 30 value 90.726044
iter 40 value 89.458304
iter 50 value 89.298199
iter 60 value 88.490295
iter 70 value 86.742615
iter 80 value 85.226272
iter 90 value 84.641366
iter 100 value 84.260255
final value 84.260255
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 118.715583
iter 10 value 94.465814
iter 20 value 92.478587
iter 30 value 88.846337
iter 40 value 88.234456
iter 50 value 87.884399
iter 60 value 87.767587
iter 70 value 87.306069
iter 80 value 86.487044
iter 90 value 84.988018
iter 100 value 84.616459
final value 84.616459
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.421754
final value 94.487336
converged
Fitting Repeat 2
# weights: 103
initial value 95.541710
final value 94.485844
converged
Fitting Repeat 3
# weights: 103
initial value 104.264472
final value 94.485917
converged
Fitting Repeat 4
# weights: 103
initial value 95.579582
iter 10 value 94.028304
iter 20 value 94.027872
final value 94.026683
converged
Fitting Repeat 5
# weights: 103
initial value 98.953376
final value 94.485973
converged
Fitting Repeat 1
# weights: 305
initial value 97.023433
iter 10 value 93.998314
iter 20 value 93.997761
iter 30 value 93.995435
iter 40 value 93.846504
iter 50 value 93.140834
iter 60 value 88.026508
iter 70 value 85.865108
iter 80 value 85.312230
iter 90 value 84.289466
iter 100 value 84.264260
final value 84.264260
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 95.904401
iter 10 value 94.489034
iter 20 value 94.484318
final value 94.484227
converged
Fitting Repeat 3
# weights: 305
initial value 97.231928
iter 10 value 94.489025
iter 20 value 94.463422
iter 30 value 91.235189
iter 40 value 90.855619
iter 50 value 90.234090
iter 60 value 90.218174
iter 70 value 88.204946
iter 80 value 87.240074
iter 90 value 86.984026
iter 100 value 86.979886
final value 86.979886
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 94.982227
iter 10 value 93.986290
iter 20 value 93.661228
iter 30 value 90.659482
iter 40 value 89.746786
iter 50 value 89.735336
iter 60 value 89.596650
iter 70 value 89.591082
iter 80 value 88.688237
iter 90 value 87.927149
iter 100 value 87.924902
final value 87.924902
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.910488
iter 10 value 93.884105
iter 20 value 93.747675
iter 30 value 93.735374
iter 40 value 93.731732
iter 50 value 93.653799
iter 60 value 92.561261
iter 70 value 88.517431
iter 80 value 87.757247
iter 90 value 87.679404
iter 100 value 87.509613
final value 87.509613
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 98.304065
iter 10 value 93.992098
iter 20 value 93.559223
iter 30 value 89.532320
iter 40 value 88.420932
iter 50 value 88.199159
iter 60 value 87.526472
iter 70 value 87.521454
iter 70 value 87.521454
final value 87.521454
converged
Fitting Repeat 2
# weights: 507
initial value 102.990546
iter 10 value 94.035575
iter 20 value 94.027602
final value 94.027153
converged
Fitting Repeat 3
# weights: 507
initial value 101.304395
iter 10 value 90.715393
iter 20 value 90.257900
iter 30 value 90.255545
iter 40 value 90.242212
iter 50 value 89.436707
iter 60 value 87.158904
iter 70 value 87.117942
iter 80 value 87.112884
iter 90 value 87.111541
iter 100 value 86.918280
final value 86.918280
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 100.955166
iter 10 value 94.035560
iter 20 value 94.029800
iter 30 value 94.026879
final value 94.026874
converged
Fitting Repeat 5
# weights: 507
initial value 97.215436
iter 10 value 94.035250
iter 20 value 93.624204
iter 30 value 91.993751
iter 40 value 91.972584
iter 50 value 91.883618
iter 60 value 91.772768
iter 70 value 91.627594
iter 80 value 91.385743
iter 90 value 87.772233
iter 100 value 87.302541
final value 87.302541
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 120.875886
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.181645
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.111451
final value 94.305882
converged
Fitting Repeat 4
# weights: 103
initial value 109.382818
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.399758
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 104.140683
iter 10 value 94.467298
iter 20 value 94.288300
iter 20 value 94.288300
iter 20 value 94.288300
final value 94.288300
converged
Fitting Repeat 2
# weights: 305
initial value 105.565292
final value 94.312038
converged
Fitting Repeat 3
# weights: 305
initial value 96.569464
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 125.595671
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 119.481267
final value 94.466823
converged
Fitting Repeat 1
# weights: 507
initial value 98.525496
iter 10 value 91.441982
iter 20 value 87.313923
final value 85.637293
converged
Fitting Repeat 2
# weights: 507
initial value 122.581486
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 99.476768
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 111.069073
final value 94.312038
converged
Fitting Repeat 5
# weights: 507
initial value 110.930798
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 97.023678
iter 10 value 94.466546
iter 20 value 91.806961
iter 30 value 85.481286
iter 40 value 85.198976
iter 50 value 85.063210
iter 60 value 81.358307
iter 70 value 81.322480
iter 80 value 81.317682
final value 81.317546
converged
Fitting Repeat 2
# weights: 103
initial value 96.763097
iter 10 value 92.673580
iter 20 value 86.875032
iter 30 value 81.199970
iter 40 value 80.929561
iter 50 value 80.888184
iter 60 value 80.732715
iter 70 value 80.671443
iter 80 value 80.668910
final value 80.668659
converged
Fitting Repeat 3
# weights: 103
initial value 97.751584
iter 10 value 94.219714
iter 20 value 85.862595
iter 30 value 82.555197
iter 40 value 81.449470
iter 50 value 81.339416
iter 60 value 81.326692
iter 70 value 81.318688
final value 81.317545
converged
Fitting Repeat 4
# weights: 103
initial value 96.689280
iter 10 value 86.741332
iter 20 value 85.541235
iter 30 value 82.666258
iter 40 value 81.439878
iter 50 value 81.337306
iter 60 value 81.271898
iter 70 value 81.262941
final value 81.262935
converged
Fitting Repeat 5
# weights: 103
initial value 100.579261
iter 10 value 94.337375
iter 20 value 90.833597
iter 30 value 83.641619
iter 40 value 83.173566
iter 50 value 82.992576
iter 60 value 82.898005
iter 70 value 82.889619
final value 82.889615
converged
Fitting Repeat 1
# weights: 305
initial value 101.153565
iter 10 value 94.834899
iter 20 value 94.370271
iter 30 value 85.163806
iter 40 value 81.697436
iter 50 value 80.136298
iter 60 value 79.383052
iter 70 value 79.156523
iter 80 value 78.974774
iter 90 value 78.810410
iter 100 value 78.613824
final value 78.613824
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.787683
iter 10 value 94.355087
iter 20 value 93.860645
iter 30 value 85.482966
iter 40 value 84.898550
iter 50 value 84.532015
iter 60 value 84.419258
iter 70 value 84.344441
iter 80 value 81.047163
iter 90 value 79.164301
iter 100 value 78.763130
final value 78.763130
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.447111
iter 10 value 94.649766
iter 20 value 94.474105
iter 30 value 93.841333
iter 40 value 93.598207
iter 50 value 90.444495
iter 60 value 87.273088
iter 70 value 85.272338
iter 80 value 80.911652
iter 90 value 79.067781
iter 100 value 78.516162
final value 78.516162
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.140401
iter 10 value 95.206872
iter 20 value 93.957158
iter 30 value 87.959790
iter 40 value 82.225254
iter 50 value 81.939816
iter 60 value 81.368656
iter 70 value 80.876538
iter 80 value 80.564128
iter 90 value 79.544479
iter 100 value 78.308484
final value 78.308484
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 110.254748
iter 10 value 94.388504
iter 20 value 85.459699
iter 30 value 81.887639
iter 40 value 80.430680
iter 50 value 78.964396
iter 60 value 78.799431
iter 70 value 78.464322
iter 80 value 78.313715
iter 90 value 78.257416
iter 100 value 78.037344
final value 78.037344
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.059644
iter 10 value 99.908585
iter 20 value 94.977585
iter 30 value 89.023494
iter 40 value 84.592294
iter 50 value 81.094130
iter 60 value 79.977431
iter 70 value 78.209673
iter 80 value 77.631934
iter 90 value 77.258687
iter 100 value 76.954737
final value 76.954737
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.088390
iter 10 value 94.714875
iter 20 value 85.747227
iter 30 value 84.856307
iter 40 value 84.177962
iter 50 value 82.614697
iter 60 value 80.755824
iter 70 value 78.757951
iter 80 value 78.298140
iter 90 value 77.846984
iter 100 value 77.216816
final value 77.216816
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 120.768799
iter 10 value 94.329801
iter 20 value 87.691363
iter 30 value 85.185509
iter 40 value 84.803493
iter 50 value 84.584834
iter 60 value 82.769539
iter 70 value 79.208798
iter 80 value 78.430604
iter 90 value 78.320972
iter 100 value 77.834881
final value 77.834881
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 119.622851
iter 10 value 92.744829
iter 20 value 85.511003
iter 30 value 82.798733
iter 40 value 81.458749
iter 50 value 79.384709
iter 60 value 78.325706
iter 70 value 77.833880
iter 80 value 77.303632
iter 90 value 77.045916
iter 100 value 76.999796
final value 76.999796
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.006234
iter 10 value 94.540338
iter 20 value 85.167095
iter 30 value 83.291138
iter 40 value 80.719596
iter 50 value 80.461527
iter 60 value 80.266999
iter 70 value 80.067514
iter 80 value 78.787235
iter 90 value 78.113759
iter 100 value 77.282001
final value 77.282001
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.470593
iter 10 value 90.906166
iter 20 value 88.076348
iter 30 value 88.053608
iter 40 value 88.053054
iter 50 value 87.881039
iter 60 value 87.874479
final value 87.874474
converged
Fitting Repeat 2
# weights: 103
initial value 95.657513
final value 94.485962
converged
Fitting Repeat 3
# weights: 103
initial value 95.757011
final value 94.485870
converged
Fitting Repeat 4
# weights: 103
initial value 103.029812
final value 94.485966
converged
Fitting Repeat 5
# weights: 103
initial value 105.942546
final value 94.468379
converged
Fitting Repeat 1
# weights: 305
initial value 98.761914
iter 10 value 93.709624
iter 20 value 92.739832
iter 30 value 92.729764
iter 40 value 92.215832
iter 50 value 91.607142
iter 60 value 91.603322
iter 70 value 91.601800
iter 80 value 91.601710
final value 91.601662
converged
Fitting Repeat 2
# weights: 305
initial value 104.540602
iter 10 value 94.488715
iter 20 value 94.484235
final value 94.484228
converged
Fitting Repeat 3
# weights: 305
initial value 100.370264
iter 10 value 94.450104
iter 20 value 94.158817
iter 30 value 93.780632
iter 40 value 93.624731
iter 50 value 93.467412
iter 60 value 87.738955
iter 70 value 81.678837
iter 80 value 81.196044
iter 90 value 80.085168
iter 100 value 79.911004
final value 79.911004
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 97.358559
iter 10 value 94.316547
iter 20 value 93.707116
iter 30 value 82.936753
iter 40 value 81.180959
iter 50 value 81.174299
iter 60 value 81.173912
iter 70 value 81.166780
iter 80 value 81.166463
iter 90 value 81.160263
iter 100 value 81.160149
final value 81.160149
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.146776
iter 10 value 94.487475
iter 20 value 93.522557
iter 30 value 82.746936
iter 40 value 81.904374
iter 50 value 81.903801
iter 60 value 81.903551
iter 70 value 81.623054
iter 80 value 81.601552
final value 81.601040
converged
Fitting Repeat 1
# weights: 507
initial value 120.351014
iter 10 value 94.476248
iter 20 value 94.468825
iter 30 value 94.468449
iter 40 value 94.428239
iter 50 value 85.741384
iter 60 value 85.293206
iter 70 value 85.293023
iter 80 value 85.263617
iter 90 value 85.263215
final value 85.263125
converged
Fitting Repeat 2
# weights: 507
initial value 101.369605
iter 10 value 94.475442
iter 20 value 92.901187
iter 30 value 85.801640
iter 40 value 85.654683
iter 50 value 85.652191
iter 60 value 83.791449
iter 70 value 79.431964
iter 80 value 77.002332
iter 90 value 76.019290
iter 100 value 75.773636
final value 75.773636
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 116.610346
iter 10 value 94.475059
iter 20 value 94.099734
iter 30 value 93.758953
iter 40 value 93.422948
iter 50 value 93.420341
iter 60 value 93.420122
iter 70 value 93.419995
iter 80 value 93.377622
final value 93.374569
converged
Fitting Repeat 4
# weights: 507
initial value 130.936310
iter 10 value 94.476712
iter 20 value 94.410324
iter 30 value 94.004390
iter 40 value 93.783552
iter 50 value 93.602729
iter 60 value 93.536954
iter 70 value 93.534937
iter 80 value 84.943443
iter 90 value 79.532668
final value 79.524775
converged
Fitting Repeat 5
# weights: 507
initial value 136.082540
iter 10 value 94.475103
iter 20 value 94.248784
iter 30 value 81.952391
iter 40 value 81.854579
iter 50 value 81.839240
iter 60 value 81.836927
final value 81.836857
converged
Fitting Repeat 1
# weights: 103
initial value 99.435388
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 99.172693
iter 10 value 91.141416
iter 20 value 90.972810
iter 30 value 86.796308
iter 40 value 83.540746
iter 50 value 83.332926
iter 60 value 82.737156
final value 82.737151
converged
Fitting Repeat 3
# weights: 103
initial value 101.276209
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.452715
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 101.207302
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 101.240180
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 95.927534
iter 10 value 94.354396
iter 10 value 94.354396
iter 10 value 94.354396
final value 94.354396
converged
Fitting Repeat 3
# weights: 305
initial value 116.831664
final value 94.354396
converged
Fitting Repeat 4
# weights: 305
initial value 102.281447
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 99.518804
final value 94.354396
converged
Fitting Repeat 1
# weights: 507
initial value 97.621116
final value 94.354396
converged
Fitting Repeat 2
# weights: 507
initial value 94.098250
iter 10 value 89.302916
iter 20 value 86.897518
final value 86.307879
converged
Fitting Repeat 3
# weights: 507
initial value 121.459240
final value 93.300000
converged
Fitting Repeat 4
# weights: 507
initial value 118.829034
final value 94.325945
converged
Fitting Repeat 5
# weights: 507
initial value 100.497463
iter 10 value 91.883053
iter 20 value 91.480928
iter 30 value 91.467848
final value 91.467840
converged
Fitting Repeat 1
# weights: 103
initial value 99.435031
iter 10 value 94.471459
iter 20 value 93.124885
iter 30 value 92.880282
iter 40 value 92.748869
iter 50 value 90.865558
iter 60 value 86.755625
iter 70 value 86.515398
iter 80 value 83.133203
iter 90 value 82.849520
iter 100 value 82.668360
final value 82.668360
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.838049
iter 10 value 94.318894
iter 20 value 85.126361
iter 30 value 83.391566
iter 40 value 82.918277
iter 50 value 82.805723
iter 60 value 82.473488
iter 70 value 82.236670
iter 80 value 81.916590
final value 81.916088
converged
Fitting Repeat 3
# weights: 103
initial value 109.814460
iter 10 value 94.520560
iter 20 value 94.458044
iter 30 value 84.259760
iter 40 value 83.326500
iter 50 value 83.165828
iter 60 value 82.668068
iter 70 value 82.574622
iter 80 value 82.539052
iter 90 value 82.352670
iter 100 value 82.327512
final value 82.327512
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 104.362632
iter 10 value 93.843748
iter 20 value 83.516673
iter 30 value 83.347691
iter 40 value 82.627461
iter 50 value 82.479290
iter 60 value 82.394461
iter 70 value 82.324942
iter 80 value 82.316328
final value 82.316286
converged
Fitting Repeat 5
# weights: 103
initial value 103.952277
iter 10 value 94.448594
iter 20 value 91.431641
iter 30 value 90.647673
iter 40 value 90.276225
iter 50 value 89.991093
iter 60 value 89.765414
iter 70 value 84.455261
iter 80 value 84.267422
iter 90 value 84.053678
iter 100 value 83.909076
final value 83.909076
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.092622
iter 10 value 95.152018
iter 20 value 88.940381
iter 30 value 85.758606
iter 40 value 84.004519
iter 50 value 81.992591
iter 60 value 80.981512
iter 70 value 80.509119
iter 80 value 80.156694
iter 90 value 80.114864
iter 100 value 80.038309
final value 80.038309
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.921926
iter 10 value 94.368651
iter 20 value 83.742788
iter 30 value 83.375428
iter 40 value 82.920462
iter 50 value 82.728580
iter 60 value 82.468151
iter 70 value 80.512327
iter 80 value 80.013034
iter 90 value 79.657618
iter 100 value 79.654518
final value 79.654518
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.652702
iter 10 value 94.519937
iter 20 value 94.480495
iter 30 value 93.678981
iter 40 value 85.340757
iter 50 value 84.380963
iter 60 value 83.210273
iter 70 value 82.067558
iter 80 value 81.213741
iter 90 value 80.989546
iter 100 value 80.941305
final value 80.941305
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.291058
iter 10 value 94.691643
iter 20 value 94.282420
iter 30 value 86.013937
iter 40 value 85.311500
iter 50 value 83.596849
iter 60 value 82.499974
iter 70 value 82.000982
iter 80 value 81.921547
iter 90 value 81.722318
iter 100 value 81.268181
final value 81.268181
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.739769
iter 10 value 94.436494
iter 20 value 90.830134
iter 30 value 86.044503
iter 40 value 82.106844
iter 50 value 81.612318
iter 60 value 81.015146
iter 70 value 80.560816
iter 80 value 80.297783
iter 90 value 80.082720
iter 100 value 79.943567
final value 79.943567
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 127.012622
iter 10 value 97.502010
iter 20 value 88.307154
iter 30 value 87.485242
iter 40 value 84.795897
iter 50 value 84.473786
iter 60 value 83.174711
iter 70 value 82.038130
iter 80 value 81.851446
iter 90 value 81.801760
iter 100 value 81.738292
final value 81.738292
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.472550
iter 10 value 92.416291
iter 20 value 86.698373
iter 30 value 84.155052
iter 40 value 82.583655
iter 50 value 81.182227
iter 60 value 80.738824
iter 70 value 80.242236
iter 80 value 80.208908
iter 90 value 80.121527
iter 100 value 79.824588
final value 79.824588
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.867975
iter 10 value 94.806697
iter 20 value 85.784784
iter 30 value 84.664472
iter 40 value 84.528382
iter 50 value 84.041840
iter 60 value 83.012972
iter 70 value 80.555049
iter 80 value 79.948065
iter 90 value 79.628925
iter 100 value 79.441978
final value 79.441978
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 121.121392
iter 10 value 94.537114
iter 20 value 93.797747
iter 30 value 89.302801
iter 40 value 84.567187
iter 50 value 83.527225
iter 60 value 81.197597
iter 70 value 79.811428
iter 80 value 79.606123
iter 90 value 79.498129
iter 100 value 79.274588
final value 79.274588
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.802865
iter 10 value 92.085441
iter 20 value 84.900501
iter 30 value 83.113101
iter 40 value 81.898036
iter 50 value 81.582580
iter 60 value 81.547711
iter 70 value 81.349031
iter 80 value 80.852315
iter 90 value 80.474065
iter 100 value 80.069323
final value 80.069323
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 115.996469
final value 94.485960
converged
Fitting Repeat 2
# weights: 103
initial value 99.469255
final value 94.485740
converged
Fitting Repeat 3
# weights: 103
initial value 98.021187
final value 94.485819
converged
Fitting Repeat 4
# weights: 103
initial value 95.636726
final value 94.485948
converged
Fitting Repeat 5
# weights: 103
initial value 102.382868
final value 94.485718
converged
Fitting Repeat 1
# weights: 305
initial value 108.088806
iter 10 value 94.517215
iter 20 value 94.504107
iter 30 value 94.027522
iter 40 value 84.675221
iter 50 value 83.663606
iter 60 value 82.582338
iter 70 value 82.579061
iter 80 value 82.537504
iter 90 value 82.501793
iter 100 value 82.498259
final value 82.498259
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.740210
iter 10 value 94.488928
iter 20 value 94.484235
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 105.879173
iter 10 value 89.237890
iter 20 value 86.705581
iter 30 value 86.673421
iter 40 value 86.041943
iter 50 value 85.969105
iter 60 value 85.967283
iter 70 value 85.964995
iter 80 value 85.964670
iter 90 value 85.963838
iter 90 value 85.963838
iter 90 value 85.963838
final value 85.963838
converged
Fitting Repeat 4
# weights: 305
initial value 100.223245
iter 10 value 94.489340
iter 20 value 94.484361
iter 30 value 93.880228
iter 40 value 83.772307
iter 50 value 82.961221
iter 60 value 82.943147
iter 70 value 82.935251
iter 80 value 82.923507
iter 90 value 82.918689
iter 100 value 82.907793
final value 82.907793
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 97.674623
iter 10 value 94.359488
iter 20 value 94.354485
final value 94.354478
converged
Fitting Repeat 1
# weights: 507
initial value 114.367906
iter 10 value 94.492653
iter 20 value 94.482934
iter 30 value 89.237328
iter 40 value 82.750717
iter 50 value 82.699734
final value 82.699516
converged
Fitting Repeat 2
# weights: 507
initial value 99.015349
iter 10 value 94.293304
iter 20 value 94.290622
iter 30 value 91.002694
iter 40 value 90.949300
iter 50 value 90.939040
iter 60 value 90.936154
iter 70 value 90.935423
iter 80 value 90.213401
iter 90 value 90.188725
iter 90 value 90.188724
iter 90 value 90.188724
final value 90.188724
converged
Fitting Repeat 3
# weights: 507
initial value 110.501501
iter 10 value 94.491354
iter 20 value 89.995937
iter 30 value 82.584218
iter 40 value 82.202427
iter 50 value 81.791500
iter 60 value 81.726138
iter 70 value 81.723102
iter 80 value 81.722260
iter 90 value 81.353913
iter 100 value 80.723586
final value 80.723586
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.726668
iter 10 value 94.487575
iter 20 value 93.077391
iter 30 value 82.940646
iter 40 value 82.420749
iter 50 value 81.975768
iter 60 value 81.039343
iter 70 value 80.818758
iter 80 value 80.808323
iter 80 value 80.808322
iter 80 value 80.808322
final value 80.808322
converged
Fitting Repeat 5
# weights: 507
initial value 114.495841
iter 10 value 93.220689
iter 20 value 93.212980
iter 30 value 93.206661
iter 40 value 93.030117
iter 50 value 83.405302
iter 60 value 80.845393
iter 70 value 79.846359
iter 80 value 79.614267
iter 90 value 78.541474
iter 100 value 78.351247
final value 78.351247
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.826510
final value 94.032967
converged
Fitting Repeat 2
# weights: 103
initial value 94.487303
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 94.289295
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 96.696219
final value 94.032967
converged
Fitting Repeat 5
# weights: 103
initial value 101.669856
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 101.317386
iter 10 value 92.134977
iter 20 value 84.898226
iter 30 value 84.838636
iter 40 value 84.806731
final value 84.806723
converged
Fitting Repeat 2
# weights: 305
initial value 102.879446
final value 94.032967
converged
Fitting Repeat 3
# weights: 305
initial value 115.918943
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 99.948241
final value 92.701658
converged
Fitting Repeat 5
# weights: 305
initial value 107.147631
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 103.014825
iter 10 value 93.890375
iter 20 value 93.858453
final value 93.855862
converged
Fitting Repeat 2
# weights: 507
initial value 101.839402
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 123.820492
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 108.991561
final value 94.032967
converged
Fitting Repeat 5
# weights: 507
initial value 114.699526
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 97.573600
iter 10 value 93.950020
iter 20 value 87.639962
iter 30 value 87.280927
iter 40 value 86.111099
iter 50 value 84.797148
iter 60 value 84.786323
iter 70 value 84.389051
iter 80 value 84.151507
iter 90 value 84.145844
final value 84.144257
converged
Fitting Repeat 2
# weights: 103
initial value 100.099928
iter 10 value 94.002141
iter 20 value 92.061927
iter 30 value 83.336653
iter 40 value 82.307512
iter 50 value 82.070393
iter 60 value 81.878474
iter 70 value 81.774711
iter 80 value 81.659765
iter 90 value 81.531527
iter 100 value 81.276251
final value 81.276251
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 101.872908
iter 10 value 94.054268
iter 20 value 88.420262
iter 30 value 85.769824
iter 40 value 84.360775
iter 50 value 83.725703
iter 60 value 83.086500
iter 70 value 82.922911
iter 80 value 82.696119
iter 90 value 82.517243
final value 82.517109
converged
Fitting Repeat 4
# weights: 103
initial value 96.435494
iter 10 value 94.068697
iter 20 value 94.043986
iter 30 value 93.306957
iter 40 value 88.035274
iter 50 value 86.322546
iter 60 value 84.502904
iter 70 value 84.398704
iter 80 value 84.379703
iter 90 value 83.863780
iter 100 value 83.838339
final value 83.838339
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 98.178425
iter 10 value 94.085319
iter 20 value 91.128986
iter 30 value 87.450385
iter 40 value 85.868473
iter 50 value 85.444612
iter 60 value 84.664719
iter 70 value 84.180179
iter 80 value 84.145403
iter 90 value 84.140413
iter 100 value 84.120933
final value 84.120933
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 115.590563
iter 10 value 94.046999
iter 20 value 93.377560
iter 30 value 85.745088
iter 40 value 82.706043
iter 50 value 81.560175
iter 60 value 81.217582
iter 70 value 81.211828
iter 80 value 81.188212
iter 90 value 81.109782
iter 100 value 80.714333
final value 80.714333
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 125.446913
iter 10 value 92.825619
iter 20 value 88.016468
iter 30 value 84.792698
iter 40 value 83.237646
iter 50 value 80.958088
iter 60 value 80.430271
iter 70 value 80.380811
iter 80 value 80.316508
iter 90 value 80.066728
iter 100 value 80.025416
final value 80.025416
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.536267
iter 10 value 94.057511
iter 20 value 93.163300
iter 30 value 92.004279
iter 40 value 87.049020
iter 50 value 86.356153
iter 60 value 84.825677
iter 70 value 84.508026
iter 80 value 82.488296
iter 90 value 81.919253
iter 100 value 81.521113
final value 81.521113
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.606645
iter 10 value 91.815922
iter 20 value 87.615030
iter 30 value 87.063213
iter 40 value 82.369228
iter 50 value 81.315600
iter 60 value 80.751520
iter 70 value 80.628064
iter 80 value 80.461804
iter 90 value 80.283623
iter 100 value 80.068870
final value 80.068870
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 111.414838
iter 10 value 94.039420
iter 20 value 93.556381
iter 30 value 85.618379
iter 40 value 84.409933
iter 50 value 84.133616
iter 60 value 82.491236
iter 70 value 81.927578
iter 80 value 81.223613
iter 90 value 80.878209
iter 100 value 80.840814
final value 80.840814
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.495099
iter 10 value 94.986417
iter 20 value 90.435753
iter 30 value 86.324903
iter 40 value 84.694205
iter 50 value 84.118810
iter 60 value 81.203373
iter 70 value 80.441061
iter 80 value 80.248778
iter 90 value 80.077541
iter 100 value 79.995225
final value 79.995225
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.417304
iter 10 value 93.230655
iter 20 value 91.848196
iter 30 value 90.638929
iter 40 value 87.010998
iter 50 value 85.397025
iter 60 value 83.678394
iter 70 value 83.387252
iter 80 value 81.611027
iter 90 value 80.413750
iter 100 value 80.135555
final value 80.135555
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 105.114735
iter 10 value 93.538147
iter 20 value 92.254414
iter 30 value 86.860786
iter 40 value 86.441951
iter 50 value 85.652924
iter 60 value 82.178163
iter 70 value 81.102690
iter 80 value 80.017080
iter 90 value 79.781242
iter 100 value 79.678657
final value 79.678657
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.556035
iter 10 value 94.030691
iter 20 value 87.902704
iter 30 value 87.323725
iter 40 value 85.356279
iter 50 value 83.911084
iter 60 value 83.703542
iter 70 value 82.552958
iter 80 value 81.062117
iter 90 value 80.573523
iter 100 value 80.290762
final value 80.290762
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 103.181369
iter 10 value 93.607398
iter 20 value 88.125068
iter 30 value 84.562761
iter 40 value 84.025185
iter 50 value 82.446317
iter 60 value 81.840171
iter 70 value 81.685903
iter 80 value 81.025614
iter 90 value 80.173497
iter 100 value 79.968249
final value 79.968249
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.404199
final value 94.054364
converged
Fitting Repeat 2
# weights: 103
initial value 97.783614
final value 94.054582
converged
Fitting Repeat 3
# weights: 103
initial value 102.527839
final value 94.054553
converged
Fitting Repeat 4
# weights: 103
initial value 99.378022
iter 10 value 89.394197
iter 20 value 88.682626
iter 30 value 87.293993
iter 40 value 84.498306
iter 50 value 84.428108
iter 60 value 84.427655
iter 70 value 83.605602
iter 80 value 83.573248
iter 90 value 83.570210
iter 100 value 83.569372
final value 83.569372
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 102.101045
final value 94.054454
converged
Fitting Repeat 1
# weights: 305
initial value 97.484872
iter 10 value 94.057988
iter 20 value 94.053083
iter 30 value 93.805888
iter 40 value 88.299080
iter 50 value 88.085128
iter 60 value 88.013212
iter 70 value 88.004308
iter 80 value 88.003306
iter 90 value 87.891692
final value 87.891025
converged
Fitting Repeat 2
# weights: 305
initial value 118.268050
iter 10 value 94.057842
iter 20 value 94.053268
iter 30 value 94.007237
iter 40 value 91.636366
iter 50 value 91.561460
iter 60 value 91.552372
iter 70 value 88.768614
iter 80 value 88.181502
iter 90 value 88.163473
iter 100 value 88.075916
final value 88.075916
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.464984
iter 10 value 94.057727
iter 20 value 94.050875
iter 30 value 91.103739
iter 40 value 90.760557
iter 50 value 90.734374
iter 60 value 90.207008
iter 70 value 89.867916
iter 80 value 89.862028
iter 90 value 89.861537
final value 89.861533
converged
Fitting Repeat 4
# weights: 305
initial value 94.605781
iter 10 value 87.229583
iter 20 value 86.816570
iter 30 value 86.812413
iter 30 value 86.812412
iter 30 value 86.812412
final value 86.812412
converged
Fitting Repeat 5
# weights: 305
initial value 100.363443
iter 10 value 94.057914
iter 20 value 94.053003
iter 30 value 86.179932
iter 40 value 83.623309
iter 50 value 83.488645
iter 60 value 82.644808
final value 82.278542
converged
Fitting Repeat 1
# weights: 507
initial value 119.948226
iter 10 value 94.041702
iter 20 value 94.033145
iter 30 value 86.949481
iter 40 value 86.670837
iter 50 value 84.815041
iter 60 value 84.710612
iter 70 value 79.685735
iter 80 value 79.375301
iter 90 value 79.334678
iter 100 value 79.325839
final value 79.325839
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 120.360526
iter 10 value 94.060280
iter 20 value 94.029206
iter 30 value 88.094757
iter 40 value 86.789143
iter 50 value 86.596893
iter 50 value 86.596892
iter 50 value 86.596892
final value 86.596892
converged
Fitting Repeat 3
# weights: 507
initial value 97.196480
iter 10 value 94.041595
iter 20 value 94.033435
iter 30 value 87.809602
iter 40 value 86.641318
iter 50 value 86.313683
iter 60 value 85.983340
iter 70 value 85.969576
iter 80 value 83.248550
iter 90 value 83.156307
final value 83.156166
converged
Fitting Repeat 4
# weights: 507
initial value 96.742774
iter 10 value 91.855002
iter 20 value 90.386289
iter 30 value 90.379118
iter 40 value 90.365952
iter 50 value 90.363913
iter 60 value 90.363831
iter 70 value 89.847132
iter 80 value 88.234406
iter 90 value 83.761588
iter 100 value 83.712536
final value 83.712536
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 97.734842
iter 10 value 94.041281
iter 20 value 94.033072
iter 30 value 93.555405
iter 40 value 87.123984
iter 50 value 83.355758
iter 60 value 81.221449
iter 70 value 79.768243
iter 80 value 79.458063
iter 90 value 79.412605
iter 100 value 79.272611
final value 79.272611
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 131.677905
iter 10 value 117.763982
iter 20 value 117.735509
iter 30 value 117.729271
final value 117.728950
converged
Fitting Repeat 2
# weights: 305
initial value 146.751430
iter 10 value 117.763480
iter 20 value 117.759034
iter 30 value 117.459892
iter 40 value 105.414665
iter 50 value 104.927554
iter 60 value 104.907580
final value 104.907336
converged
Fitting Repeat 3
# weights: 305
initial value 134.190810
iter 10 value 117.764239
iter 20 value 117.760890
iter 30 value 107.773885
iter 40 value 107.208051
iter 50 value 106.851061
iter 60 value 105.022974
final value 104.980064
converged
Fitting Repeat 4
# weights: 305
initial value 129.816843
iter 10 value 117.763828
iter 20 value 117.543085
iter 30 value 109.909603
iter 40 value 108.246751
iter 40 value 108.246751
final value 108.145827
converged
Fitting Repeat 5
# weights: 305
initial value 136.874368
iter 10 value 117.242110
iter 20 value 117.009882
iter 30 value 116.984645
iter 40 value 116.982926
iter 50 value 115.225834
iter 60 value 115.208582
iter 70 value 115.116784
iter 80 value 115.114692
iter 80 value 115.114692
iter 80 value 115.114691
final value 115.114691
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 -- Wed Mar 11 00:25:27 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
39.961 1.467 95.387
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 33.774 | 0.424 | 34.235 | |
| FreqInteractors | 0.479 | 0.027 | 0.507 | |
| calculateAAC | 0.040 | 0.000 | 0.041 | |
| calculateAutocor | 0.346 | 0.014 | 0.361 | |
| calculateCTDC | 0.080 | 0.000 | 0.081 | |
| calculateCTDD | 0.548 | 0.001 | 0.549 | |
| calculateCTDT | 0.191 | 0.006 | 0.197 | |
| calculateCTriad | 0.380 | 0.011 | 0.391 | |
| calculateDC | 0.084 | 0.003 | 0.087 | |
| calculateF | 0.314 | 0.000 | 0.315 | |
| calculateKSAAP | 0.105 | 0.000 | 0.105 | |
| calculateQD_Sm | 1.869 | 0.010 | 1.880 | |
| calculateTC | 1.496 | 0.022 | 1.519 | |
| calculateTC_Sm | 0.250 | 0.002 | 0.252 | |
| corr_plot | 34.749 | 0.533 | 35.301 | |
| enrichfindP | 0.508 | 0.043 | 11.573 | |
| enrichfind_hp | 0.049 | 0.000 | 1.038 | |
| enrichplot | 0.549 | 0.002 | 0.551 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.431 | 0.037 | 3.009 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0.001 | 0.000 | 0.002 | |
| get_positivePPI | 0.000 | 0.000 | 0.001 | |
| impute_missing_data | 0.001 | 0.000 | 0.001 | |
| plotPPI | 0.086 | 0.000 | 0.087 | |
| pred_ensembel | 12.900 | 0.238 | 11.914 | |
| var_imp | 33.416 | 0.720 | 34.142 | |