| Back to Multiple platform build/check report for BioC 3.21: simplified long |
|
This page was generated on 2025-10-09 11:41 -0400 (Thu, 09 Oct 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | 4.5.1 (2025-06-13) -- "Great Square Root" | 4832 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.5.1 RC (2025-06-05 r88288) -- "Great Square Root" | 4613 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.5.1 Patched (2025-06-14 r88325) -- "Great Square Root" | 4554 |
| kunpeng2 | Linux (openEuler 24.03 LTS) | aarch64 | R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences" | 4585 |
| 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 997/2341 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.14.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | ERROR | skipped | |||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | ERROR | skipped | skipped | |||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | ERROR | skipped | skipped | |||||||||
| kunpeng2 | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. - See Martin Grigorov's blog post for how to debug Linux ARM64 related issues on a x86_64 host. |
| Package: HPiP |
| Version: 1.14.0 |
| Command: /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.14.0.tar.gz |
| StartedAt: 2025-10-07 10:30:07 -0000 (Tue, 07 Oct 2025) |
| EndedAt: 2025-10-07 10:36:56 -0000 (Tue, 07 Oct 2025) |
| EllapsedTime: 408.6 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/R/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R/site-library --no-vignettes --timings HPiP_1.14.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2025-02-19 r87757)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
aarch64-unknown-linux-gnu-gcc (GCC) 14.2.0
GNU Fortran (GCC) 14.2.0
* running under: openEuler 24.03 (LTS-SP1)
* using session charset: UTF-8
* using option ‘--no-vignettes’
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.14.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
Package unavailable to check Rd xrefs: ‘ftrCOOL’
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
var_imp 39.443 0.348 39.870
corr_plot 37.159 0.303 37.531
FSmethod 36.885 0.279 37.240
pred_ensembel 18.357 0.336 17.560
enrichfindP 0.487 0.032 18.863
getFASTA 0.073 0.008 5.189
* 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 running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.21-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/R/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/R/R-devel_2025-02-19/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.14.0’ ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R Under development (unstable) (2025-02-19 r87757) -- "Unsuffered Consequences"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: aarch64-unknown-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 101.694696
iter 10 value 90.105107
iter 20 value 88.340027
iter 30 value 87.710367
iter 40 value 87.696794
final value 87.696368
converged
Fitting Repeat 2
# weights: 103
initial value 94.781758
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.366191
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 99.159234
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 102.521043
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 96.557925
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 117.574114
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 95.506641
final value 93.867392
converged
Fitting Repeat 4
# weights: 305
initial value 97.029598
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 107.140796
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 105.499434
iter 10 value 94.012575
iter 20 value 93.867813
final value 93.867391
converged
Fitting Repeat 2
# weights: 507
initial value 112.183961
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 98.174714
iter 10 value 93.940228
iter 20 value 90.122452
final value 90.122449
converged
Fitting Repeat 4
# weights: 507
initial value 143.714316
iter 10 value 93.875801
final value 93.867391
converged
Fitting Repeat 5
# weights: 507
initial value 99.265918
iter 10 value 91.737425
iter 20 value 86.189601
iter 30 value 86.165909
iter 30 value 86.165909
iter 30 value 86.165909
final value 86.165909
converged
Fitting Repeat 1
# weights: 103
initial value 107.419673
iter 10 value 94.056592
iter 20 value 93.814794
iter 30 value 93.379056
iter 40 value 92.969417
iter 50 value 83.623987
iter 60 value 82.805759
iter 70 value 81.974061
iter 80 value 81.898912
final value 81.897304
converged
Fitting Repeat 2
# weights: 103
initial value 99.950302
iter 10 value 93.984809
iter 20 value 92.926265
iter 30 value 85.087653
iter 40 value 82.463702
iter 50 value 82.291252
iter 60 value 81.992202
iter 70 value 81.876421
iter 80 value 81.866539
final value 81.866505
converged
Fitting Repeat 3
# weights: 103
initial value 106.846880
iter 10 value 93.483085
iter 20 value 85.370674
iter 30 value 83.510854
iter 40 value 82.172733
iter 50 value 81.091142
iter 60 value 80.507074
iter 70 value 80.447676
final value 80.447384
converged
Fitting Repeat 4
# weights: 103
initial value 97.291451
iter 10 value 94.060914
iter 20 value 94.050537
iter 30 value 92.894341
iter 40 value 89.475517
iter 50 value 82.699326
iter 60 value 82.470835
iter 70 value 81.770362
iter 80 value 81.667045
iter 90 value 81.522546
iter 100 value 81.496104
final value 81.496104
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 100.022183
iter 10 value 93.991011
iter 20 value 92.538101
iter 30 value 86.164154
iter 40 value 84.281356
iter 50 value 83.794676
iter 60 value 83.287802
iter 70 value 82.540747
iter 80 value 82.442654
final value 82.418710
converged
Fitting Repeat 1
# weights: 305
initial value 99.308715
iter 10 value 85.792254
iter 20 value 85.350030
iter 30 value 85.255428
iter 40 value 85.107217
iter 50 value 82.512681
iter 60 value 81.847833
iter 70 value 80.951718
iter 80 value 80.054809
iter 90 value 79.594584
iter 100 value 79.437008
final value 79.437008
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.580327
iter 10 value 94.045991
iter 20 value 89.598924
iter 30 value 83.350472
iter 40 value 81.741276
iter 50 value 81.249899
iter 60 value 81.103635
iter 70 value 81.084042
iter 80 value 81.024174
iter 90 value 80.892575
iter 100 value 80.877405
final value 80.877405
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 118.099499
iter 10 value 94.040655
iter 20 value 87.373099
iter 30 value 83.151310
iter 40 value 82.198858
iter 50 value 81.652832
iter 60 value 80.941592
iter 70 value 80.062655
iter 80 value 79.546962
iter 90 value 79.262651
iter 100 value 79.195089
final value 79.195089
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 99.416101
iter 10 value 93.550756
iter 20 value 86.694540
iter 30 value 82.984679
iter 40 value 81.388784
iter 50 value 80.819291
iter 60 value 80.397424
iter 70 value 79.540512
iter 80 value 79.345274
iter 90 value 79.305596
iter 100 value 79.294626
final value 79.294626
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 108.424243
iter 10 value 94.118127
iter 20 value 93.598860
iter 30 value 91.261643
iter 40 value 81.255152
iter 50 value 80.363149
iter 60 value 79.629689
iter 70 value 79.556516
iter 80 value 79.504146
iter 90 value 79.119381
iter 100 value 78.762497
final value 78.762497
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 108.712541
iter 10 value 94.129579
iter 20 value 93.394702
iter 30 value 88.542818
iter 40 value 82.872062
iter 50 value 81.277680
iter 60 value 80.544244
iter 70 value 80.247670
iter 80 value 79.782183
iter 90 value 79.400494
iter 100 value 79.229128
final value 79.229128
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.133228
iter 10 value 89.304068
iter 20 value 85.969661
iter 30 value 84.067263
iter 40 value 82.222335
iter 50 value 81.069393
iter 60 value 79.987601
iter 70 value 79.419175
iter 80 value 79.060310
iter 90 value 78.926909
iter 100 value 78.884567
final value 78.884567
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.582660
iter 10 value 94.437037
iter 20 value 88.622912
iter 30 value 82.675905
iter 40 value 82.380289
iter 50 value 81.915655
iter 60 value 81.406196
iter 70 value 81.099912
iter 80 value 80.421493
iter 90 value 79.872080
iter 100 value 79.770183
final value 79.770183
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.745587
iter 10 value 93.637669
iter 20 value 85.946839
iter 30 value 84.002164
iter 40 value 80.876965
iter 50 value 79.606815
iter 60 value 79.393685
iter 70 value 79.030999
iter 80 value 78.983789
iter 90 value 78.922184
iter 100 value 78.656493
final value 78.656493
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.865888
iter 10 value 94.533891
iter 20 value 85.750656
iter 30 value 82.968653
iter 40 value 82.522339
iter 50 value 82.253303
iter 60 value 82.160230
iter 70 value 81.476100
iter 80 value 80.653526
iter 90 value 79.946277
iter 100 value 79.620580
final value 79.620580
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.333681
final value 94.054693
converged
Fitting Repeat 2
# weights: 103
initial value 100.922960
final value 94.054321
converged
Fitting Repeat 3
# weights: 103
initial value 99.889263
final value 94.054538
converged
Fitting Repeat 4
# weights: 103
initial value 102.077022
final value 94.054488
converged
Fitting Repeat 5
# weights: 103
initial value 95.633968
iter 10 value 87.233224
iter 20 value 83.281062
iter 30 value 83.236757
iter 40 value 83.228380
final value 83.228266
converged
Fitting Repeat 1
# weights: 305
initial value 99.318900
iter 10 value 93.938755
iter 20 value 93.887914
iter 30 value 92.386683
iter 40 value 92.385977
iter 50 value 84.807989
iter 60 value 84.367167
iter 70 value 84.299565
iter 80 value 84.298945
iter 90 value 84.298580
iter 100 value 84.293577
final value 84.293577
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.841636
iter 10 value 94.057768
final value 94.052979
converged
Fitting Repeat 3
# weights: 305
initial value 108.631431
iter 10 value 94.031013
iter 20 value 94.027709
iter 30 value 85.180295
iter 40 value 84.287649
final value 84.287572
converged
Fitting Repeat 4
# weights: 305
initial value 106.341146
iter 10 value 94.057783
iter 20 value 93.981902
iter 30 value 91.143020
iter 40 value 91.132623
iter 50 value 91.115156
iter 60 value 91.112686
iter 70 value 91.104681
iter 80 value 83.508466
iter 90 value 79.889931
iter 100 value 79.104848
final value 79.104848
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 95.773176
iter 10 value 94.057750
final value 94.052917
converged
Fitting Repeat 1
# weights: 507
initial value 96.826416
iter 10 value 93.876108
iter 20 value 93.665324
iter 30 value 81.010701
iter 40 value 79.676818
iter 50 value 79.582001
iter 60 value 79.501285
iter 70 value 79.500731
iter 80 value 79.483059
iter 90 value 78.381143
iter 100 value 77.764028
final value 77.764028
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 116.654794
iter 10 value 93.875898
iter 20 value 93.872719
iter 30 value 93.871380
iter 40 value 93.859310
iter 50 value 85.342408
iter 60 value 84.084108
final value 84.077855
converged
Fitting Repeat 3
# weights: 507
initial value 106.154187
iter 10 value 93.715973
iter 20 value 84.872113
iter 30 value 84.812330
iter 40 value 84.476815
iter 50 value 84.474983
iter 60 value 84.465420
final value 84.465418
converged
Fitting Repeat 4
# weights: 507
initial value 109.603789
iter 10 value 94.061126
iter 20 value 94.053139
iter 30 value 82.701449
iter 40 value 81.320504
final value 81.320385
converged
Fitting Repeat 5
# weights: 507
initial value 118.614127
iter 10 value 94.084402
iter 20 value 93.905265
iter 30 value 81.744572
iter 40 value 81.638754
iter 50 value 81.563044
iter 60 value 81.557732
iter 70 value 81.393066
iter 80 value 81.249569
iter 90 value 81.241526
iter 100 value 80.990893
final value 80.990893
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.132525
final value 94.466823
converged
Fitting Repeat 2
# weights: 103
initial value 96.233725
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 101.667277
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 102.378055
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.693844
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 102.294909
final value 94.312038
converged
Fitting Repeat 2
# weights: 305
initial value 95.850160
iter 10 value 91.059335
iter 20 value 85.610686
iter 30 value 85.540860
iter 40 value 85.539793
iter 50 value 85.409330
iter 60 value 84.846883
iter 70 value 84.845709
iter 80 value 84.766966
final value 84.759731
converged
Fitting Repeat 3
# weights: 305
initial value 101.087911
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 109.337918
final value 94.466823
converged
Fitting Repeat 5
# weights: 305
initial value 105.358475
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 106.961205
iter 10 value 89.517378
iter 20 value 88.912380
iter 30 value 88.863174
final value 88.673745
converged
Fitting Repeat 2
# weights: 507
initial value 105.784170
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 101.755041
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 96.344097
final value 94.320299
converged
Fitting Repeat 5
# weights: 507
initial value 118.108443
final value 94.052434
converged
Fitting Repeat 1
# weights: 103
initial value 98.002350
iter 10 value 94.503183
iter 20 value 93.343992
iter 30 value 88.850888
iter 40 value 88.669747
iter 50 value 88.189705
iter 60 value 87.336357
iter 70 value 86.885197
iter 80 value 86.742584
iter 90 value 86.673611
iter 100 value 86.432577
final value 86.432577
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 95.900222
iter 10 value 88.511306
iter 20 value 88.087635
iter 30 value 87.439085
iter 40 value 86.388137
iter 50 value 85.728415
iter 60 value 85.584726
iter 70 value 85.536353
final value 85.535095
converged
Fitting Repeat 3
# weights: 103
initial value 99.750990
iter 10 value 94.175756
iter 20 value 93.755004
iter 30 value 93.725506
iter 40 value 93.723892
iter 50 value 92.240375
iter 60 value 88.248406
iter 70 value 87.584448
iter 80 value 87.068885
iter 90 value 85.581389
iter 100 value 85.398170
final value 85.398170
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 103.731684
iter 10 value 94.486595
iter 20 value 93.807052
iter 30 value 87.703980
iter 40 value 87.009865
iter 50 value 86.711728
iter 60 value 86.190562
iter 70 value 85.997602
iter 80 value 85.952960
iter 90 value 85.951476
iter 90 value 85.951476
final value 85.951476
converged
Fitting Repeat 5
# weights: 103
initial value 100.406370
iter 10 value 94.486419
iter 20 value 94.052194
iter 30 value 93.829490
iter 40 value 93.782646
iter 50 value 93.724579
iter 60 value 93.229707
iter 70 value 91.053630
iter 80 value 89.468896
iter 90 value 88.388359
iter 100 value 87.336821
final value 87.336821
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 103.232790
iter 10 value 94.517570
iter 20 value 94.460859
iter 30 value 93.959203
iter 40 value 93.914136
iter 50 value 88.263101
iter 60 value 87.397449
iter 70 value 85.807966
iter 80 value 85.403643
iter 90 value 84.732886
iter 100 value 83.828797
final value 83.828797
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.084256
iter 10 value 94.447220
iter 20 value 93.915895
iter 30 value 93.760519
iter 40 value 92.283379
iter 50 value 91.847879
iter 60 value 89.660746
iter 70 value 87.405908
iter 80 value 86.410695
iter 90 value 84.907057
iter 100 value 84.035270
final value 84.035270
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.793120
iter 10 value 94.112788
iter 20 value 89.166135
iter 30 value 88.045528
iter 40 value 85.251874
iter 50 value 84.199901
iter 60 value 83.858533
iter 70 value 83.201109
iter 80 value 82.746048
iter 90 value 82.643109
iter 100 value 82.462908
final value 82.462908
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.747501
iter 10 value 94.712245
iter 20 value 93.791351
iter 30 value 89.178527
iter 40 value 88.610154
iter 50 value 88.386464
iter 60 value 87.479047
iter 70 value 86.620072
iter 80 value 86.097451
iter 90 value 85.210312
iter 100 value 84.030638
final value 84.030638
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.151450
iter 10 value 94.366065
iter 20 value 91.232679
iter 30 value 90.112045
iter 40 value 87.115094
iter 50 value 84.887528
iter 60 value 83.977082
iter 70 value 83.134489
iter 80 value 82.501331
iter 90 value 82.307682
iter 100 value 82.227388
final value 82.227388
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 125.580314
iter 10 value 94.753632
iter 20 value 89.723517
iter 30 value 85.735001
iter 40 value 84.195576
iter 50 value 83.784727
iter 60 value 83.625384
iter 70 value 83.551901
iter 80 value 82.943436
iter 90 value 82.159396
iter 100 value 81.946671
final value 81.946671
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.153789
iter 10 value 94.484055
iter 20 value 93.425066
iter 30 value 92.583313
iter 40 value 91.859945
iter 50 value 87.772703
iter 60 value 86.771221
iter 70 value 85.462225
iter 80 value 85.127715
iter 90 value 84.783236
iter 100 value 84.301297
final value 84.301297
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 111.422500
iter 10 value 94.489215
iter 20 value 94.068673
iter 30 value 93.926968
iter 40 value 93.789482
iter 50 value 93.343468
iter 60 value 92.531962
iter 70 value 92.212951
iter 80 value 92.100861
iter 90 value 90.385153
iter 100 value 88.117036
final value 88.117036
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.913081
iter 10 value 94.549901
iter 20 value 93.891504
iter 30 value 86.883541
iter 40 value 85.289286
iter 50 value 84.521272
iter 60 value 83.219754
iter 70 value 82.992604
iter 80 value 82.565699
iter 90 value 82.227832
iter 100 value 82.094881
final value 82.094881
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.301632
iter 10 value 95.417799
iter 20 value 91.079265
iter 30 value 87.195806
iter 40 value 84.926738
iter 50 value 84.050556
iter 60 value 83.498199
iter 70 value 83.264069
iter 80 value 82.799323
iter 90 value 82.431925
iter 100 value 82.346227
final value 82.346227
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.239989
final value 94.457205
converged
Fitting Repeat 2
# weights: 103
initial value 105.140319
final value 94.485904
converged
Fitting Repeat 3
# weights: 103
initial value 102.202954
iter 10 value 94.485783
iter 20 value 94.439068
iter 30 value 93.767499
iter 40 value 93.762630
final value 93.762627
converged
Fitting Repeat 4
# weights: 103
initial value 97.109444
final value 94.485935
converged
Fitting Repeat 5
# weights: 103
initial value 103.787927
final value 94.485719
converged
Fitting Repeat 1
# weights: 305
initial value 97.372690
iter 10 value 91.842489
iter 20 value 88.244175
iter 30 value 86.854476
iter 40 value 86.827652
iter 50 value 86.761380
iter 60 value 85.480220
iter 70 value 84.337547
iter 80 value 84.335789
iter 90 value 84.331464
iter 100 value 83.072576
final value 83.072576
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 95.837368
iter 10 value 94.488955
iter 20 value 94.481909
iter 30 value 94.093447
iter 40 value 94.010426
iter 50 value 93.950382
final value 93.910134
converged
Fitting Repeat 3
# weights: 305
initial value 95.490973
iter 10 value 94.485893
iter 20 value 86.525071
iter 30 value 86.510584
iter 40 value 85.746206
iter 50 value 85.744683
iter 60 value 85.743289
iter 70 value 85.286245
final value 85.286239
converged
Fitting Repeat 4
# weights: 305
initial value 100.746609
iter 10 value 94.489661
iter 20 value 94.484607
iter 30 value 93.953335
iter 40 value 92.841125
final value 92.836008
converged
Fitting Repeat 5
# weights: 305
initial value 99.777178
iter 10 value 94.488890
iter 20 value 94.480221
iter 30 value 93.892180
iter 40 value 93.871837
final value 93.871823
converged
Fitting Repeat 1
# weights: 507
initial value 105.750084
iter 10 value 94.113072
iter 20 value 94.106017
iter 30 value 93.372488
iter 40 value 85.981584
iter 50 value 84.493871
iter 60 value 82.025406
iter 70 value 81.209627
iter 80 value 80.905093
iter 90 value 80.650624
iter 100 value 80.024774
final value 80.024774
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 97.377899
iter 10 value 89.416674
iter 20 value 87.604497
iter 30 value 87.582585
iter 40 value 87.580128
iter 50 value 87.573776
iter 60 value 87.573555
final value 87.573481
converged
Fitting Repeat 3
# weights: 507
initial value 115.468889
iter 10 value 94.492746
iter 20 value 94.484297
final value 94.484256
converged
Fitting Repeat 4
# weights: 507
initial value 115.949036
iter 10 value 94.249460
iter 20 value 88.893518
iter 30 value 88.487492
iter 40 value 88.339045
iter 50 value 88.266698
iter 60 value 86.359064
iter 70 value 85.128462
iter 80 value 84.816814
iter 90 value 84.619300
iter 100 value 84.349281
final value 84.349281
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 99.662018
iter 10 value 94.098695
iter 20 value 93.918331
iter 30 value 93.913547
iter 40 value 93.909947
final value 93.909700
converged
Fitting Repeat 1
# weights: 103
initial value 98.890608
iter 10 value 93.244227
final value 93.183861
converged
Fitting Repeat 2
# weights: 103
initial value 98.850550
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 97.392675
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 102.643931
final value 93.836066
converged
Fitting Repeat 5
# weights: 103
initial value 105.916309
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 124.124035
iter 10 value 93.836066
iter 10 value 93.836066
iter 10 value 93.836066
final value 93.836066
converged
Fitting Repeat 2
# weights: 305
initial value 97.158880
iter 10 value 93.836066
iter 10 value 93.836066
iter 10 value 93.836066
final value 93.836066
converged
Fitting Repeat 3
# weights: 305
initial value 99.878519
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 101.777909
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 106.006325
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 103.348262
iter 10 value 92.138926
final value 91.952024
converged
Fitting Repeat 2
# weights: 507
initial value 95.934857
final value 93.836066
converged
Fitting Repeat 3
# weights: 507
initial value 102.482387
iter 10 value 93.283951
iter 10 value 93.283951
iter 10 value 93.283951
final value 93.283951
converged
Fitting Repeat 4
# weights: 507
initial value 120.685285
final value 93.836066
converged
Fitting Repeat 5
# weights: 507
initial value 99.222397
iter 10 value 84.269477
iter 20 value 83.237046
iter 30 value 83.157830
final value 83.157794
converged
Fitting Repeat 1
# weights: 103
initial value 96.421727
iter 10 value 94.053588
iter 20 value 93.371292
iter 30 value 93.325848
iter 40 value 89.961264
iter 50 value 85.968789
iter 60 value 84.962417
iter 70 value 81.136152
iter 80 value 80.715620
iter 90 value 80.262384
iter 100 value 79.499088
final value 79.499088
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 102.471374
iter 10 value 94.056444
iter 20 value 93.355477
iter 30 value 93.322882
iter 40 value 92.396621
iter 50 value 85.692602
iter 60 value 82.151849
iter 70 value 81.939739
iter 80 value 81.532308
iter 90 value 81.218000
iter 100 value 81.086350
final value 81.086350
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 99.188296
iter 10 value 94.022896
iter 20 value 93.340277
iter 30 value 93.303784
iter 40 value 91.763337
iter 50 value 85.956463
iter 60 value 84.417445
iter 70 value 83.970458
iter 80 value 83.775484
iter 90 value 83.707321
iter 100 value 83.227251
final value 83.227251
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.592545
iter 10 value 94.055111
iter 20 value 93.372405
iter 30 value 93.337862
iter 40 value 93.304287
iter 50 value 89.785494
iter 60 value 85.451748
iter 70 value 82.343893
iter 80 value 81.390848
iter 90 value 81.283660
iter 100 value 81.210716
final value 81.210716
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 108.114334
iter 10 value 93.439962
iter 20 value 90.790344
iter 30 value 90.220835
iter 40 value 90.146718
iter 50 value 90.138616
final value 90.138542
converged
Fitting Repeat 1
# weights: 305
initial value 119.729001
iter 10 value 96.692426
iter 20 value 93.901562
iter 30 value 86.467878
iter 40 value 84.573489
iter 50 value 81.244051
iter 60 value 80.408853
iter 70 value 79.822563
iter 80 value 79.410676
iter 90 value 79.354259
iter 100 value 79.250922
final value 79.250922
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 118.019294
iter 10 value 90.332290
iter 20 value 85.329832
iter 30 value 83.928966
iter 40 value 79.365544
iter 50 value 78.672360
iter 60 value 78.358477
iter 70 value 78.229805
iter 80 value 78.151174
iter 90 value 78.074861
iter 100 value 78.036879
final value 78.036879
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.242530
iter 10 value 93.155436
iter 20 value 83.648627
iter 30 value 82.043761
iter 40 value 80.773314
iter 50 value 78.946150
iter 60 value 78.560773
iter 70 value 78.302602
iter 80 value 78.176901
iter 90 value 78.031358
iter 100 value 78.025300
final value 78.025300
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.171266
iter 10 value 93.976321
iter 20 value 88.529304
iter 30 value 88.125082
iter 40 value 86.938691
iter 50 value 81.429799
iter 60 value 80.441124
iter 70 value 79.214794
iter 80 value 78.514770
iter 90 value 78.256860
iter 100 value 78.193343
final value 78.193343
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 114.458136
iter 10 value 93.859860
iter 20 value 90.324994
iter 30 value 85.820621
iter 40 value 84.766420
iter 50 value 81.524797
iter 60 value 79.654769
iter 70 value 79.006570
iter 80 value 78.474903
iter 90 value 78.233387
iter 100 value 78.111483
final value 78.111483
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 131.299627
iter 10 value 96.655787
iter 20 value 90.942448
iter 30 value 87.134698
iter 40 value 83.662279
iter 50 value 82.061596
iter 60 value 80.854832
iter 70 value 79.510783
iter 80 value 78.858770
iter 90 value 78.236184
iter 100 value 78.005415
final value 78.005415
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.216022
iter 10 value 95.034719
iter 20 value 92.269050
iter 30 value 81.414481
iter 40 value 80.833705
iter 50 value 79.769260
iter 60 value 79.528437
iter 70 value 78.602910
iter 80 value 77.925028
iter 90 value 77.571542
iter 100 value 77.438086
final value 77.438086
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 131.544632
iter 10 value 94.028624
iter 20 value 90.187598
iter 30 value 85.617143
iter 40 value 83.707202
iter 50 value 81.188804
iter 60 value 80.450658
iter 70 value 79.798162
iter 80 value 79.350162
iter 90 value 79.294749
iter 100 value 79.223021
final value 79.223021
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.800447
iter 10 value 94.514611
iter 20 value 84.713702
iter 30 value 83.297769
iter 40 value 80.530888
iter 50 value 79.043919
iter 60 value 78.809620
iter 70 value 78.283503
iter 80 value 77.967672
iter 90 value 77.819919
iter 100 value 77.733659
final value 77.733659
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.556600
iter 10 value 94.189030
iter 20 value 87.492592
iter 30 value 85.112076
iter 40 value 83.418241
iter 50 value 82.002104
iter 60 value 81.115485
iter 70 value 80.391679
iter 80 value 78.969873
iter 90 value 78.072659
iter 100 value 77.921385
final value 77.921385
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.001460
iter 10 value 94.054678
final value 94.053054
converged
Fitting Repeat 2
# weights: 103
initial value 95.767108
iter 10 value 94.054576
iter 20 value 94.052928
final value 94.052919
converged
Fitting Repeat 3
# weights: 103
initial value 104.379430
final value 94.054621
converged
Fitting Repeat 4
# weights: 103
initial value 94.511690
final value 94.054717
converged
Fitting Repeat 5
# weights: 103
initial value 94.021572
iter 10 value 93.058457
iter 20 value 93.057558
final value 93.057547
converged
Fitting Repeat 1
# weights: 305
initial value 101.389012
iter 10 value 94.057563
iter 20 value 94.052934
final value 94.052918
converged
Fitting Repeat 2
# weights: 305
initial value 98.805564
iter 10 value 93.840908
iter 20 value 93.836259
iter 30 value 86.044289
iter 40 value 84.564717
iter 50 value 84.301279
iter 60 value 84.300320
iter 60 value 84.300320
final value 84.300320
converged
Fitting Repeat 3
# weights: 305
initial value 95.330030
iter 10 value 94.058251
iter 20 value 93.887397
iter 30 value 82.275566
iter 40 value 78.336477
iter 50 value 77.558852
iter 60 value 76.828412
iter 70 value 76.801180
final value 76.801158
converged
Fitting Repeat 4
# weights: 305
initial value 108.741274
iter 10 value 93.841363
iter 20 value 93.836386
iter 30 value 93.738589
iter 40 value 90.214574
iter 50 value 83.928012
iter 60 value 83.923829
iter 70 value 83.745452
iter 80 value 83.517173
iter 90 value 83.516425
final value 83.515247
converged
Fitting Repeat 5
# weights: 305
initial value 113.390321
iter 10 value 92.105773
iter 20 value 87.749117
iter 30 value 87.507795
iter 40 value 86.943129
iter 50 value 86.887336
final value 86.886654
converged
Fitting Repeat 1
# weights: 507
initial value 108.990619
iter 10 value 94.063451
iter 20 value 87.950889
iter 30 value 84.699587
iter 40 value 83.057143
iter 50 value 82.845919
iter 60 value 82.844208
iter 70 value 82.835919
iter 80 value 82.834142
final value 82.833850
converged
Fitting Repeat 2
# weights: 507
initial value 102.729593
iter 10 value 94.060815
iter 20 value 93.929056
iter 30 value 82.203971
iter 40 value 80.622500
iter 50 value 80.288933
iter 60 value 80.038844
iter 70 value 79.677555
iter 80 value 79.648611
iter 90 value 79.648550
final value 79.648546
converged
Fitting Repeat 3
# weights: 507
initial value 108.239366
iter 10 value 94.060723
iter 20 value 93.731854
iter 30 value 83.835994
iter 40 value 82.005376
iter 50 value 81.078409
iter 60 value 79.794909
iter 70 value 78.702179
iter 80 value 78.257262
iter 90 value 77.971989
iter 100 value 77.933498
final value 77.933498
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.312007
iter 10 value 94.061386
iter 20 value 93.795234
iter 30 value 86.482450
iter 40 value 86.086250
iter 50 value 85.341510
iter 60 value 84.410584
iter 70 value 84.355748
iter 80 value 83.547822
iter 90 value 83.075916
iter 100 value 83.069881
final value 83.069881
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 117.101409
iter 10 value 86.450872
iter 20 value 84.567091
iter 30 value 84.492762
iter 40 value 84.375346
iter 50 value 84.367212
iter 60 value 84.365560
iter 70 value 84.359260
iter 80 value 84.258103
iter 90 value 84.224811
iter 100 value 84.224111
final value 84.224111
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.184909
iter 10 value 94.484217
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 103.304478
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 124.021007
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.351052
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 100.412955
final value 94.026542
converged
Fitting Repeat 1
# weights: 305
initial value 105.249757
iter 10 value 89.467625
iter 20 value 89.455283
final value 89.455279
converged
Fitting Repeat 2
# weights: 305
initial value 94.822054
final value 94.026542
converged
Fitting Repeat 3
# weights: 305
initial value 95.500804
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 112.901567
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 109.827974
final value 93.668704
converged
Fitting Repeat 1
# weights: 507
initial value 95.566648
iter 10 value 94.015240
final value 94.015226
converged
Fitting Repeat 2
# weights: 507
initial value 102.301381
iter 10 value 94.026552
final value 94.026542
converged
Fitting Repeat 3
# weights: 507
initial value 106.300284
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 101.453888
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 95.764281
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 99.222038
iter 10 value 94.468541
iter 20 value 94.000514
iter 30 value 91.260629
iter 40 value 88.631395
iter 50 value 86.467706
iter 60 value 83.344066
iter 70 value 82.669996
iter 80 value 81.775731
iter 90 value 81.750127
iter 100 value 81.747239
final value 81.747239
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 101.251192
iter 10 value 94.488530
iter 20 value 94.328280
iter 30 value 94.216109
iter 40 value 92.890941
iter 50 value 88.009189
iter 60 value 87.567418
iter 70 value 84.471695
iter 80 value 84.228855
iter 90 value 84.159389
final value 84.159333
converged
Fitting Repeat 3
# weights: 103
initial value 94.485365
iter 10 value 91.309970
iter 20 value 90.964399
iter 30 value 90.939866
final value 90.937855
converged
Fitting Repeat 4
# weights: 103
initial value 101.555056
iter 10 value 94.489650
iter 20 value 93.926330
iter 30 value 93.875351
iter 40 value 90.516903
iter 50 value 87.864216
iter 60 value 85.650753
iter 70 value 82.457370
iter 80 value 82.232318
iter 90 value 82.007338
iter 100 value 81.975132
final value 81.975132
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 103.554699
iter 10 value 94.042174
iter 20 value 87.586167
iter 30 value 86.990330
iter 40 value 86.086925
iter 50 value 85.766036
iter 60 value 85.635526
final value 85.635355
converged
Fitting Repeat 1
# weights: 305
initial value 101.654155
iter 10 value 94.960270
iter 20 value 94.701525
iter 30 value 94.085048
iter 40 value 89.713747
iter 50 value 88.378335
iter 60 value 88.175608
iter 70 value 87.949782
iter 80 value 85.881536
iter 90 value 85.104380
iter 100 value 84.774027
final value 84.774027
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.270922
iter 10 value 93.546272
iter 20 value 88.154472
iter 30 value 84.485159
iter 40 value 82.715100
iter 50 value 81.878079
iter 60 value 81.511749
iter 70 value 81.240843
iter 80 value 81.159012
iter 90 value 80.995397
iter 100 value 80.983259
final value 80.983259
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.426793
iter 10 value 94.452800
iter 20 value 85.994409
iter 30 value 85.765304
iter 40 value 85.164622
iter 50 value 84.330518
iter 60 value 82.622277
iter 70 value 81.850610
iter 80 value 81.467641
iter 90 value 81.278857
iter 100 value 81.016103
final value 81.016103
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 108.194487
iter 10 value 95.694865
iter 20 value 92.462039
iter 30 value 88.219270
iter 40 value 86.498987
iter 50 value 85.459377
iter 60 value 82.224040
iter 70 value 81.954939
iter 80 value 81.790290
iter 90 value 81.597844
iter 100 value 81.532216
final value 81.532216
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.043926
iter 10 value 94.494134
iter 20 value 94.373287
iter 30 value 86.111967
iter 40 value 84.765499
iter 50 value 81.779612
iter 60 value 81.553862
iter 70 value 81.276415
iter 80 value 81.156454
iter 90 value 81.083349
iter 100 value 80.683263
final value 80.683263
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 120.810995
iter 10 value 95.064483
iter 20 value 89.661252
iter 30 value 88.827974
iter 40 value 84.218163
iter 50 value 82.522821
iter 60 value 81.645330
iter 70 value 81.509833
iter 80 value 81.273385
iter 90 value 81.160982
iter 100 value 81.114392
final value 81.114392
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 111.860636
iter 10 value 94.006099
iter 20 value 93.377019
iter 30 value 87.758184
iter 40 value 86.641965
iter 50 value 85.746944
iter 60 value 84.599262
iter 70 value 81.842535
iter 80 value 81.375273
iter 90 value 81.219726
iter 100 value 80.900554
final value 80.900554
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.290808
iter 10 value 94.742218
iter 20 value 93.758206
iter 30 value 88.533322
iter 40 value 86.803671
iter 50 value 85.633618
iter 60 value 83.702375
iter 70 value 82.352288
iter 80 value 81.768311
iter 90 value 81.483452
iter 100 value 81.305700
final value 81.305700
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 121.719143
iter 10 value 94.105360
iter 20 value 85.814964
iter 30 value 84.077142
iter 40 value 83.556963
iter 50 value 82.889924
iter 60 value 82.207079
iter 70 value 81.912470
iter 80 value 81.672859
iter 90 value 81.549367
iter 100 value 81.187882
final value 81.187882
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 110.772598
iter 10 value 96.524395
iter 20 value 89.292764
iter 30 value 84.272386
iter 40 value 82.939962
iter 50 value 82.248816
iter 60 value 81.443618
iter 70 value 81.161750
iter 80 value 81.099034
iter 90 value 80.922228
iter 100 value 80.852977
final value 80.852977
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 118.865294
final value 94.486090
converged
Fitting Repeat 2
# weights: 103
initial value 99.062991
final value 94.485693
converged
Fitting Repeat 3
# weights: 103
initial value 102.967597
final value 94.485909
converged
Fitting Repeat 4
# weights: 103
initial value 102.331229
final value 94.485715
converged
Fitting Repeat 5
# weights: 103
initial value 103.729699
final value 94.485614
converged
Fitting Repeat 1
# weights: 305
initial value 94.916178
iter 10 value 94.031593
iter 20 value 93.663418
iter 30 value 87.379440
iter 40 value 85.182142
iter 50 value 85.127545
iter 60 value 85.126181
final value 85.126147
converged
Fitting Repeat 2
# weights: 305
initial value 96.093287
iter 10 value 94.486641
iter 20 value 94.482464
iter 30 value 93.823343
iter 40 value 88.758703
iter 50 value 85.701070
iter 60 value 85.454596
iter 70 value 85.229969
iter 80 value 85.202963
iter 90 value 85.200396
iter 100 value 85.199314
final value 85.199314
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 95.684654
iter 10 value 94.489192
final value 94.484222
converged
Fitting Repeat 4
# weights: 305
initial value 97.855576
iter 10 value 94.036389
iter 20 value 94.035039
iter 30 value 94.031735
iter 40 value 93.788224
final value 93.739090
converged
Fitting Repeat 5
# weights: 305
initial value 96.455259
iter 10 value 94.032013
iter 20 value 94.027556
iter 30 value 94.021043
iter 40 value 93.800652
iter 50 value 93.791820
iter 60 value 93.791630
iter 70 value 93.791325
iter 80 value 93.790965
iter 90 value 93.784228
iter 100 value 92.661777
final value 92.661777
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.915363
iter 10 value 94.492599
iter 20 value 94.484292
iter 20 value 94.484291
iter 20 value 94.484291
final value 94.484291
converged
Fitting Repeat 2
# weights: 507
initial value 107.121665
iter 10 value 94.035397
iter 20 value 92.936394
iter 30 value 85.841445
iter 40 value 85.340357
iter 50 value 85.302307
iter 60 value 85.201846
iter 70 value 85.197949
iter 80 value 85.196564
iter 90 value 85.191066
iter 100 value 84.589975
final value 84.589975
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.528881
iter 10 value 94.449979
iter 20 value 94.339673
iter 30 value 93.811321
iter 40 value 93.804189
final value 93.795960
converged
Fitting Repeat 4
# weights: 507
initial value 97.547558
iter 10 value 94.492439
iter 20 value 94.483636
iter 30 value 94.027647
iter 30 value 94.027647
iter 30 value 94.027647
final value 94.027647
converged
Fitting Repeat 5
# weights: 507
initial value 102.906378
iter 10 value 94.492571
iter 20 value 93.794037
iter 30 value 90.359227
iter 40 value 88.946103
iter 50 value 88.943122
iter 60 value 88.941154
iter 70 value 88.779317
iter 80 value 88.275887
iter 90 value 88.252099
final value 88.251037
converged
Fitting Repeat 1
# weights: 103
initial value 108.546339
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 96.130360
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 97.524579
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.121578
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.433284
final value 94.026542
converged
Fitting Repeat 1
# weights: 305
initial value 101.662431
iter 10 value 90.839613
iter 20 value 88.229952
iter 30 value 88.226407
final value 88.226400
converged
Fitting Repeat 2
# weights: 305
initial value 106.303636
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 105.148521
iter 10 value 92.120996
iter 20 value 91.471330
final value 91.471322
converged
Fitting Repeat 4
# weights: 305
initial value 99.847540
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 95.505739
final value 94.026542
converged
Fitting Repeat 1
# weights: 507
initial value 114.593968
final value 94.026542
converged
Fitting Repeat 2
# weights: 507
initial value 99.726322
final value 94.252920
converged
Fitting Repeat 3
# weights: 507
initial value 99.854477
final value 94.046703
converged
Fitting Repeat 4
# weights: 507
initial value 103.242907
iter 10 value 92.256866
iter 20 value 87.051389
iter 30 value 86.983960
final value 86.983942
converged
Fitting Repeat 5
# weights: 507
initial value 96.666213
iter 10 value 94.021984
iter 20 value 94.019156
iter 20 value 94.019155
iter 20 value 94.019155
final value 94.019155
converged
Fitting Repeat 1
# weights: 103
initial value 103.633799
iter 10 value 94.242534
iter 20 value 88.831103
iter 30 value 84.307807
iter 40 value 83.227682
iter 50 value 82.468969
iter 60 value 82.139221
iter 70 value 82.085528
final value 82.085345
converged
Fitting Repeat 2
# weights: 103
initial value 102.720043
iter 10 value 94.148159
iter 20 value 94.094770
iter 30 value 89.351900
iter 40 value 87.634025
iter 50 value 87.259169
iter 60 value 86.453319
iter 70 value 83.336407
iter 80 value 81.605236
iter 90 value 81.550008
final value 81.549993
converged
Fitting Repeat 3
# weights: 103
initial value 101.558139
iter 10 value 94.495033
iter 20 value 94.489289
iter 30 value 94.353578
iter 40 value 94.180428
iter 50 value 94.129143
iter 60 value 94.127979
iter 70 value 94.092492
iter 80 value 85.936139
iter 90 value 84.183818
iter 100 value 83.871555
final value 83.871555
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 96.126473
iter 10 value 94.488343
iter 20 value 92.084162
iter 30 value 88.159249
iter 40 value 83.337943
iter 50 value 82.737179
iter 60 value 82.158207
iter 70 value 82.085765
final value 82.085345
converged
Fitting Repeat 5
# weights: 103
initial value 97.519959
iter 10 value 93.086839
iter 20 value 84.215676
iter 30 value 83.814740
iter 40 value 82.811340
iter 50 value 82.421293
iter 60 value 82.307773
iter 70 value 82.177946
iter 80 value 82.085473
final value 82.085345
converged
Fitting Repeat 1
# weights: 305
initial value 100.676090
iter 10 value 94.099958
iter 20 value 88.648033
iter 30 value 85.604696
iter 40 value 81.613480
iter 50 value 81.102432
iter 60 value 79.986488
iter 70 value 79.751657
iter 80 value 79.458345
iter 90 value 79.348061
iter 100 value 79.261831
final value 79.261831
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.572515
iter 10 value 94.928996
iter 20 value 89.987633
iter 30 value 88.231995
iter 40 value 84.006029
iter 50 value 83.474413
iter 60 value 82.241074
iter 70 value 82.051851
iter 80 value 81.605832
iter 90 value 81.007070
iter 100 value 80.391607
final value 80.391607
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 114.049500
iter 10 value 94.300575
iter 20 value 88.392793
iter 30 value 86.494501
iter 40 value 85.664989
iter 50 value 82.146544
iter 60 value 81.139555
iter 70 value 80.623443
iter 80 value 80.585071
iter 90 value 80.099067
iter 100 value 79.784320
final value 79.784320
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 101.088430
iter 10 value 91.549771
iter 20 value 87.336771
iter 30 value 82.969749
iter 40 value 82.579006
iter 50 value 82.408759
iter 60 value 82.053282
iter 70 value 80.990441
iter 80 value 80.390424
iter 90 value 80.305581
iter 100 value 80.229064
final value 80.229064
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 109.604179
iter 10 value 94.524829
iter 20 value 94.126322
iter 30 value 87.904254
iter 40 value 84.146248
iter 50 value 82.849090
iter 60 value 81.671104
iter 70 value 80.245674
iter 80 value 79.561874
iter 90 value 79.460303
iter 100 value 79.320472
final value 79.320472
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.798541
iter 10 value 94.489593
iter 20 value 94.125846
iter 30 value 86.255002
iter 40 value 84.780601
iter 50 value 83.354177
iter 60 value 82.679059
iter 70 value 81.326343
iter 80 value 81.048531
iter 90 value 80.841675
iter 100 value 79.995109
final value 79.995109
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.356050
iter 10 value 93.521312
iter 20 value 87.985584
iter 30 value 86.418451
iter 40 value 85.496342
iter 50 value 84.700502
iter 60 value 84.088739
iter 70 value 83.889556
iter 80 value 83.538102
iter 90 value 82.326095
iter 100 value 80.632498
final value 80.632498
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 118.943432
iter 10 value 95.673784
iter 20 value 90.528898
iter 30 value 84.449771
iter 40 value 82.822874
iter 50 value 81.516717
iter 60 value 80.337906
iter 70 value 79.581010
iter 80 value 79.442146
iter 90 value 79.325303
iter 100 value 79.236769
final value 79.236769
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 115.395966
iter 10 value 96.182024
iter 20 value 95.696626
iter 30 value 84.412829
iter 40 value 83.887000
iter 50 value 81.618956
iter 60 value 80.505878
iter 70 value 80.132529
iter 80 value 79.890297
iter 90 value 79.643934
iter 100 value 79.367825
final value 79.367825
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 121.799489
iter 10 value 94.940516
iter 20 value 86.010484
iter 30 value 84.929047
iter 40 value 83.584880
iter 50 value 81.719557
iter 60 value 79.893576
iter 70 value 79.392698
iter 80 value 79.308602
iter 90 value 79.254151
iter 100 value 79.230412
final value 79.230412
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.108714
final value 94.028513
converged
Fitting Repeat 2
# weights: 103
initial value 95.877801
final value 94.486005
converged
Fitting Repeat 3
# weights: 103
initial value 99.805199
final value 94.485858
converged
Fitting Repeat 4
# weights: 103
initial value 104.217508
final value 94.485747
converged
Fitting Repeat 5
# weights: 103
initial value 95.126636
final value 94.486022
converged
Fitting Repeat 1
# weights: 305
initial value 104.884619
iter 10 value 94.488590
iter 20 value 94.483171
iter 30 value 94.026773
iter 30 value 94.026772
iter 30 value 94.026772
final value 94.026772
converged
Fitting Repeat 2
# weights: 305
initial value 100.503364
iter 10 value 94.489298
iter 20 value 93.448815
iter 30 value 88.116629
iter 40 value 88.115598
iter 50 value 86.592489
iter 60 value 85.715790
iter 70 value 85.707346
iter 80 value 85.706133
iter 90 value 85.045813
final value 85.011904
converged
Fitting Repeat 3
# weights: 305
initial value 103.553066
iter 10 value 94.488961
iter 20 value 91.242564
iter 30 value 83.938730
iter 40 value 83.917843
final value 83.917819
converged
Fitting Repeat 4
# weights: 305
initial value 109.234711
iter 10 value 82.585804
iter 20 value 80.624140
iter 30 value 80.605126
iter 40 value 80.604277
iter 50 value 80.594422
iter 60 value 80.341239
iter 70 value 80.147114
iter 80 value 80.145673
final value 80.145501
converged
Fitting Repeat 5
# weights: 305
initial value 114.420064
iter 10 value 94.489706
iter 20 value 93.267740
iter 30 value 88.789525
iter 40 value 86.828275
iter 50 value 86.780011
iter 60 value 86.779342
iter 70 value 85.030402
iter 80 value 84.835636
iter 80 value 84.835636
final value 84.835636
converged
Fitting Repeat 1
# weights: 507
initial value 117.026468
iter 10 value 94.492207
iter 20 value 94.459684
iter 30 value 94.327544
iter 40 value 91.142170
iter 50 value 89.503606
iter 60 value 83.502786
iter 70 value 83.026148
iter 80 value 83.025400
iter 90 value 81.990789
iter 100 value 81.258221
final value 81.258221
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 97.200852
iter 10 value 94.487671
iter 20 value 92.538818
iter 30 value 85.435644
iter 40 value 85.360737
iter 50 value 84.901357
iter 60 value 84.811681
iter 70 value 84.811185
final value 84.809945
converged
Fitting Repeat 3
# weights: 507
initial value 112.299343
iter 10 value 94.034671
iter 20 value 94.028087
iter 30 value 91.054830
iter 40 value 90.268766
iter 50 value 90.145842
final value 90.145675
converged
Fitting Repeat 4
# weights: 507
initial value 105.330270
iter 10 value 94.296870
iter 20 value 94.230054
iter 30 value 93.673308
iter 40 value 83.729405
iter 50 value 83.024335
final value 83.020741
converged
Fitting Repeat 5
# weights: 507
initial value 117.729164
iter 10 value 94.492023
iter 20 value 94.294773
iter 30 value 93.260312
iter 40 value 84.946677
iter 50 value 81.909242
iter 60 value 79.413488
iter 70 value 79.208637
iter 80 value 79.205571
iter 90 value 79.204670
iter 100 value 79.202906
final value 79.202906
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 123.134462
iter 10 value 117.569273
iter 20 value 117.554939
iter 30 value 117.513573
final value 117.512718
converged
Fitting Repeat 2
# weights: 305
initial value 135.214162
iter 10 value 117.763993
iter 20 value 117.093551
iter 30 value 108.552155
final value 108.506922
converged
Fitting Repeat 3
# weights: 305
initial value 138.172284
iter 10 value 115.317790
iter 20 value 114.331063
iter 30 value 113.880615
iter 40 value 113.712503
iter 50 value 113.694809
iter 60 value 113.622961
final value 113.622714
converged
Fitting Repeat 4
# weights: 305
initial value 142.902465
iter 10 value 117.895275
iter 20 value 117.762068
final value 117.759726
converged
Fitting Repeat 5
# weights: 305
initial value 129.010629
iter 10 value 117.734977
iter 20 value 116.649720
iter 30 value 110.127045
iter 40 value 109.305021
iter 50 value 108.975930
iter 60 value 108.886399
iter 70 value 108.635803
final value 108.635251
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 -- Tue Oct 7 10:36:51 2025
***********************************************
Number of test functions: 7
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7
Number of errors: 0
Number of failures: 0
Warning messages:
1: `repeats` has no meaning for this resampling method.
2: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
53.844 1.463 137.094
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 36.885 | 0.279 | 37.240 | |
| FreqInteractors | 0.273 | 0.024 | 0.298 | |
| calculateAAC | 0.044 | 0.004 | 0.048 | |
| calculateAutocor | 0.693 | 0.020 | 0.717 | |
| calculateCTDC | 0.097 | 0.000 | 0.097 | |
| calculateCTDD | 0.736 | 0.000 | 0.738 | |
| calculateCTDT | 0.249 | 0.012 | 0.262 | |
| calculateCTriad | 0.47 | 0.00 | 0.47 | |
| calculateDC | 0.129 | 0.000 | 0.129 | |
| calculateF | 0.434 | 0.004 | 0.439 | |
| calculateKSAAP | 0.140 | 0.004 | 0.145 | |
| calculateQD_Sm | 2.355 | 0.020 | 2.381 | |
| calculateTC | 2.406 | 0.028 | 2.439 | |
| calculateTC_Sm | 0.331 | 0.000 | 0.332 | |
| corr_plot | 37.159 | 0.303 | 37.531 | |
| enrichfindP | 0.487 | 0.032 | 18.863 | |
| enrichfind_hp | 0.077 | 0.004 | 1.349 | |
| enrichplot | 0.469 | 0.064 | 0.534 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.073 | 0.008 | 5.189 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0.002 | 0.000 | 0.002 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.002 | 0.000 | 0.002 | |
| plotPPI | 0.079 | 0.008 | 0.088 | |
| pred_ensembel | 18.357 | 0.336 | 17.560 | |
| var_imp | 39.443 | 0.348 | 39.870 | |