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This page was generated on 2024-05-04 11:40:38 -0400 (Sat, 04 May 2024).

HostnameOSArch (*)R versionInstalled pkgs
nebbiolo1Linux (Ubuntu 22.04.3 LTS)x86_644.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" 4753
palomino3Windows Server 2022 Datacenterx644.4.0 beta (2024-04-15 r86425 ucrt) -- "Puppy Cup" 4486
lconwaymacOS 12.7.1 Montereyx86_644.4.0 beta (2024-04-14 r86421) -- "Puppy Cup" 4519
kunpeng2Linux (openEuler 22.03 LTS-SP1)aarch644.4.0 beta (2024-04-15 r86425) -- "Puppy Cup" 4479
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 987/2300HostnameOS / ArchINSTALLBUILDCHECKBUILD BIN
HPiP 1.10.0  (landing page)
Matineh Rahmatbakhsh
Snapshot Date: 2024-05-03 14:00:19 -0400 (Fri, 03 May 2024)
git_url: https://git.bioconductor.org/packages/HPiP
git_branch: RELEASE_3_19
git_last_commit: 09dc3c1
git_last_commit_date: 2024-04-30 11:37:16 -0400 (Tue, 30 Apr 2024)
nebbiolo1Linux (Ubuntu 22.04.3 LTS) / x86_64  OK    OK    OK  UNNEEDED, same version is already published
palomino3Windows Server 2022 Datacenter / x64  OK    OK    OK    OK  UNNEEDED, same version is already published
lconwaymacOS 12.7.1 Monterey / x86_64  OK    OK    OK    OK  UNNEEDED, same version is already published
kunpeng2Linux (openEuler 22.03 LTS-SP1) / aarch64  OK    OK    OK  
kjohnson3macOS 13.6.5 Ventura / arm64see weekly results here

CHECK results for HPiP on kunpeng2


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.

raw results


Summary

Package: HPiP
Version: 1.10.0
Command: /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R-beta-2024-04-15_r86425/site-library --no-vignettes --timings HPiP_1.10.0.tar.gz
StartedAt: 2024-05-04 08:28:47 -0000 (Sat, 04 May 2024)
EndedAt: 2024-05-04 08:35:10 -0000 (Sat, 04 May 2024)
EllapsedTime: 383.7 seconds
RetCode: 0
Status:   OK  
CheckDir: HPiP.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/R/R-beta-2024-04-15_r86425/site-library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck’
* using R version 4.4.0 beta (2024-04-15 r86425)
* using platform: aarch64-unknown-linux-gnu
* R was compiled by
    gcc (GCC) 10.3.1
    GNU Fortran (GCC) 10.3.1
* running under: openEuler 22.03 (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 ‘1.10.0’
* 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 ... NOTE
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       38.610  0.879  39.559
FSmethod      38.281  0.603  38.979
corr_plot     38.315  0.467  38.856
pred_ensembel 18.408  0.553  16.580
enrichfindP    0.537  0.028  39.625
getFASTA       0.094  0.000   8.377
* 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: 3 NOTEs
See
  ‘/home/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log’
for details.


Installation output

HPiP.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/R/R-beta-2024-04-15_r86425/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/R/R-beta-2024-04-15_r86425/site-library’
* installing *source* package ‘HPiP’ ...
** 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)

Tests output

HPiP.Rcheck/tests/runTests.Rout


R version 4.4.0 beta (2024-04-15 r86425) -- "Puppy Cup"
Copyright (C) 2024 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 94.042735 
iter  10 value 90.542533
iter  20 value 90.536100
iter  30 value 86.562652
iter  40 value 86.276513
final  value 86.276423 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.743168 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.759702 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.131352 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.639470 
final  value 94.051984 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.031676 
iter  10 value 84.735579
iter  20 value 84.535909
iter  30 value 84.529116
iter  40 value 84.529006
iter  40 value 84.529006
iter  40 value 84.529006
final  value 84.529006 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.383251 
iter  10 value 93.893252
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.725165 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 105.539936 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 105.158924 
iter  10 value 88.431629
iter  20 value 87.611788
iter  30 value 87.609931
final  value 87.609756 
converged
Fitting Repeat 1 

# weights:  507
initial  value 99.640688 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.509211 
iter  10 value 92.357864
iter  20 value 87.368462
iter  30 value 87.366699
final  value 87.366697 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.847986 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.725001 
iter  10 value 93.913370
final  value 93.912644 
converged
Fitting Repeat 5 

# weights:  507
initial  value 144.154933 
iter  10 value 93.238541
final  value 93.238538 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.839715 
iter  10 value 94.101959
iter  20 value 94.024412
iter  30 value 93.742915
iter  40 value 93.737550
iter  50 value 93.728492
iter  60 value 93.721742
iter  70 value 93.606950
iter  80 value 89.423895
iter  90 value 86.944591
iter 100 value 86.140544
final  value 86.140544 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.946674 
iter  10 value 94.055560
iter  20 value 93.843557
iter  30 value 93.685007
iter  40 value 93.678433
iter  50 value 93.256604
iter  60 value 86.924528
iter  70 value 86.149502
iter  80 value 85.522371
iter  90 value 85.518000
final  value 85.517972 
converged
Fitting Repeat 3 

# weights:  103
initial  value 107.492905 
iter  10 value 94.050218
iter  20 value 93.526613
iter  30 value 93.167655
iter  40 value 91.476153
iter  50 value 87.882139
iter  60 value 87.254334
iter  70 value 86.949526
final  value 86.779199 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.034041 
iter  10 value 94.056352
iter  20 value 93.778101
iter  30 value 89.905709
iter  40 value 87.952667
iter  50 value 87.392622
iter  60 value 87.160167
iter  70 value 86.873326
iter  80 value 86.788299
iter  90 value 86.788224
final  value 86.788049 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.818867 
iter  10 value 93.643482
iter  20 value 89.378036
iter  30 value 86.576980
iter  40 value 85.717997
iter  50 value 85.520382
final  value 85.517971 
converged
Fitting Repeat 1 

# weights:  305
initial  value 112.143908 
iter  10 value 95.125495
iter  20 value 93.352523
iter  30 value 92.510835
iter  40 value 92.134944
iter  50 value 91.861785
iter  60 value 91.545925
iter  70 value 86.621282
iter  80 value 85.145146
iter  90 value 84.193315
iter 100 value 83.920435
final  value 83.920435 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.777201 
iter  10 value 94.162229
iter  20 value 94.054315
iter  30 value 92.697387
iter  40 value 88.659302
iter  50 value 86.638623
iter  60 value 84.624590
iter  70 value 84.390084
iter  80 value 84.223383
iter  90 value 84.145299
iter 100 value 84.016197
final  value 84.016197 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.044352 
iter  10 value 93.576031
iter  20 value 89.445250
iter  30 value 87.451961
iter  40 value 84.777174
iter  50 value 84.290845
iter  60 value 83.051877
iter  70 value 82.691738
iter  80 value 82.322484
iter  90 value 82.233391
iter 100 value 82.147120
final  value 82.147120 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 106.875313 
iter  10 value 93.668896
iter  20 value 88.213268
iter  30 value 85.645311
iter  40 value 84.606296
iter  50 value 83.370493
iter  60 value 83.090578
iter  70 value 82.634154
iter  80 value 82.569109
iter  90 value 82.460714
iter 100 value 82.455137
final  value 82.455137 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 109.523032 
iter  10 value 94.081710
iter  20 value 87.104573
iter  30 value 86.160254
iter  40 value 85.375912
iter  50 value 84.719407
iter  60 value 84.424969
iter  70 value 84.129762
iter  80 value 83.934643
iter  90 value 83.456578
iter 100 value 83.299204
final  value 83.299204 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.090913 
iter  10 value 94.134936
iter  20 value 93.645464
iter  30 value 91.461368
iter  40 value 86.169110
iter  50 value 84.612353
iter  60 value 83.023876
iter  70 value 82.765803
iter  80 value 82.552812
iter  90 value 82.475960
iter 100 value 82.170595
final  value 82.170595 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.451537 
iter  10 value 94.190410
iter  20 value 92.876095
iter  30 value 91.576344
iter  40 value 86.975971
iter  50 value 84.881479
iter  60 value 84.567369
iter  70 value 83.990820
iter  80 value 83.643282
iter  90 value 83.071565
iter 100 value 82.921581
final  value 82.921581 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 144.348499 
iter  10 value 93.967921
iter  20 value 88.041872
iter  30 value 85.595759
iter  40 value 85.384118
iter  50 value 84.459492
iter  60 value 84.068065
iter  70 value 83.773979
iter  80 value 83.429594
iter  90 value 83.020680
iter 100 value 82.819865
final  value 82.819865 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.783235 
iter  10 value 94.302744
iter  20 value 93.657169
iter  30 value 93.441456
iter  40 value 92.472831
iter  50 value 88.809687
iter  60 value 87.588820
iter  70 value 87.106107
iter  80 value 86.458094
iter  90 value 84.994313
iter 100 value 84.367240
final  value 84.367240 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.028745 
iter  10 value 94.059494
iter  20 value 87.520289
iter  30 value 86.096563
iter  40 value 85.642492
iter  50 value 85.261125
iter  60 value 85.122820
iter  70 value 84.942932
iter  80 value 84.601751
iter  90 value 83.414627
iter 100 value 82.453130
final  value 82.453130 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.913141 
final  value 94.054587 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.670001 
final  value 93.914460 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.122610 
final  value 94.054631 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.772611 
iter  10 value 94.054575
iter  20 value 94.052925
iter  30 value 87.065866
iter  40 value 85.735394
iter  50 value 85.521438
iter  60 value 85.513902
final  value 85.513878 
converged
Fitting Repeat 5 

# weights:  103
initial  value 105.098525 
iter  10 value 94.054704
final  value 94.052983 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.636217 
iter  10 value 94.057757
iter  20 value 94.036792
iter  30 value 86.717588
iter  40 value 86.035151
iter  50 value 85.820816
iter  60 value 85.272224
final  value 85.271929 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.202566 
iter  10 value 94.058690
iter  20 value 94.038034
iter  30 value 86.345235
iter  40 value 85.256360
iter  50 value 85.242793
iter  60 value 85.233492
iter  70 value 84.177557
iter  80 value 84.172722
iter  90 value 84.172634
iter 100 value 84.172485
final  value 84.172485 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 98.155302 
iter  10 value 94.057289
iter  20 value 94.010080
iter  30 value 85.470495
iter  40 value 85.273226
iter  50 value 85.248220
iter  60 value 85.243947
iter  70 value 85.241153
final  value 85.241146 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.594649 
iter  10 value 94.057150
iter  20 value 93.579799
iter  30 value 92.768811
iter  40 value 88.017477
iter  50 value 87.605072
iter  60 value 87.428278
iter  70 value 87.425379
iter  80 value 87.424608
iter  90 value 87.420437
iter 100 value 86.008472
final  value 86.008472 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 98.678531 
iter  10 value 94.057893
iter  20 value 93.377509
iter  30 value 89.657151
iter  40 value 88.568749
iter  50 value 86.725387
iter  60 value 86.037013
iter  70 value 86.034132
iter  80 value 86.032309
iter  90 value 86.025720
iter 100 value 85.270170
final  value 85.270170 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 126.941935 
iter  10 value 93.921807
iter  20 value 92.119390
iter  30 value 91.987693
iter  40 value 90.046684
iter  50 value 83.402833
iter  60 value 82.531043
iter  70 value 82.527904
iter  80 value 82.526321
iter  90 value 82.523105
iter 100 value 82.511460
final  value 82.511460 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 104.611778 
iter  10 value 93.543558
iter  20 value 93.502757
iter  30 value 93.411324
iter  40 value 92.316650
iter  50 value 91.798394
iter  60 value 91.798233
final  value 91.798231 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.775012 
iter  10 value 94.060414
iter  20 value 93.540277
iter  30 value 93.346373
final  value 93.346213 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.156406 
iter  10 value 93.590612
iter  20 value 93.429599
iter  30 value 90.769872
iter  40 value 85.928436
iter  50 value 85.527368
iter  60 value 85.517438
iter  70 value 85.505556
iter  80 value 85.337736
iter  90 value 84.510458
iter 100 value 84.366292
final  value 84.366292 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.824500 
iter  10 value 93.591177
iter  20 value 93.584715
final  value 93.583694 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.665502 
iter  10 value 94.052665
final  value 94.052655 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.428549 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.703680 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.334264 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.655406 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.193406 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.640020 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 102.153043 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.966369 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.162242 
final  value 94.052448 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.835993 
final  value 94.007737 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.341289 
final  value 94.035088 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.653962 
iter  10 value 82.903532
iter  20 value 82.857856
iter  30 value 82.857178
final  value 82.857143 
converged
Fitting Repeat 4 

# weights:  507
initial  value 98.396561 
final  value 94.035088 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.368934 
iter  10 value 93.763746
iter  10 value 93.763745
iter  10 value 93.763745
final  value 93.763745 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.117256 
iter  10 value 94.057579
iter  20 value 94.022889
iter  30 value 83.557787
iter  40 value 82.882735
iter  50 value 82.546569
iter  60 value 81.733221
iter  70 value 80.596349
iter  80 value 80.559111
final  value 80.559099 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.830663 
iter  10 value 93.783718
iter  20 value 87.912746
iter  30 value 84.947177
iter  40 value 81.248050
iter  50 value 80.205259
iter  60 value 80.099460
iter  70 value 80.089509
final  value 80.089505 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.821335 
iter  10 value 93.708613
iter  20 value 88.397048
iter  30 value 85.347104
iter  40 value 82.534125
iter  50 value 81.334399
iter  60 value 80.690757
iter  70 value 80.617809
iter  80 value 80.601421
iter  90 value 80.597070
iter 100 value 80.596561
final  value 80.596561 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 117.279142 
iter  10 value 94.803870
iter  20 value 94.028157
iter  30 value 88.222058
iter  40 value 86.244292
iter  50 value 83.349867
iter  60 value 82.025924
iter  70 value 81.574323
final  value 81.574274 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.330921 
iter  10 value 94.057879
iter  20 value 94.055567
iter  30 value 92.098273
iter  40 value 89.195542
iter  50 value 88.889066
iter  60 value 85.569280
iter  70 value 82.451284
iter  80 value 81.111244
iter  90 value 80.614998
iter 100 value 80.583924
final  value 80.583924 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.089138 
iter  10 value 93.580191
iter  20 value 88.694177
iter  30 value 84.572607
iter  40 value 81.854317
iter  50 value 79.503125
iter  60 value 78.915477
iter  70 value 78.217793
iter  80 value 78.022110
iter  90 value 77.899654
iter 100 value 77.792486
final  value 77.792486 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 104.342058 
iter  10 value 87.263609
iter  20 value 82.815510
iter  30 value 82.571541
iter  40 value 79.114294
iter  50 value 78.720163
iter  60 value 78.598091
iter  70 value 78.532079
iter  80 value 78.084553
iter  90 value 77.845149
iter 100 value 77.654780
final  value 77.654780 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.384943 
iter  10 value 94.324345
iter  20 value 94.086234
iter  30 value 93.955697
iter  40 value 83.165241
iter  50 value 81.736426
iter  60 value 81.206567
iter  70 value 80.759627
iter  80 value 79.901916
iter  90 value 78.876324
iter 100 value 77.702668
final  value 77.702668 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 101.368827 
iter  10 value 95.853665
iter  20 value 94.595354
iter  30 value 93.758483
iter  40 value 86.029324
iter  50 value 81.477844
iter  60 value 81.111850
iter  70 value 79.493326
iter  80 value 78.242616
iter  90 value 77.886140
iter 100 value 77.485118
final  value 77.485118 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.101884 
iter  10 value 93.862685
iter  20 value 93.632382
iter  30 value 93.496535
iter  40 value 90.263454
iter  50 value 84.480755
iter  60 value 80.516790
iter  70 value 78.963633
iter  80 value 78.112590
iter  90 value 77.900042
iter 100 value 77.701132
final  value 77.701132 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.586945 
iter  10 value 95.840032
iter  20 value 91.942987
iter  30 value 89.105530
iter  40 value 88.416955
iter  50 value 85.807194
iter  60 value 83.565795
iter  70 value 80.067340
iter  80 value 78.619506
iter  90 value 78.055362
iter 100 value 77.984820
final  value 77.984820 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 113.872474 
iter  10 value 94.231796
iter  20 value 83.488890
iter  30 value 82.366789
iter  40 value 81.205441
iter  50 value 80.780451
iter  60 value 80.458966
iter  70 value 80.269838
iter  80 value 80.220520
iter  90 value 79.465582
iter 100 value 78.291387
final  value 78.291387 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.398947 
iter  10 value 94.070393
iter  20 value 91.838157
iter  30 value 84.118172
iter  40 value 82.373995
iter  50 value 81.857288
iter  60 value 80.117314
iter  70 value 79.260839
iter  80 value 79.191966
iter  90 value 79.097694
iter 100 value 78.506429
final  value 78.506429 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 120.085108 
iter  10 value 94.283633
iter  20 value 93.839706
iter  30 value 83.610178
iter  40 value 81.230444
iter  50 value 80.570278
iter  60 value 79.568541
iter  70 value 78.401617
iter  80 value 77.856889
iter  90 value 77.741025
iter 100 value 77.639935
final  value 77.639935 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.100922 
iter  10 value 94.059404
iter  20 value 92.762907
iter  30 value 92.328218
iter  40 value 90.314515
iter  50 value 86.094857
iter  60 value 82.146533
iter  70 value 79.160035
iter  80 value 78.652412
iter  90 value 77.615790
iter 100 value 77.524643
final  value 77.524643 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 104.478277 
iter  10 value 91.273733
final  value 91.256244 
converged
Fitting Repeat 2 

# weights:  103
initial  value 112.257857 
final  value 94.054285 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.498678 
final  value 94.054507 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.407395 
iter  10 value 94.010414
iter  20 value 94.008771
iter  30 value 89.541597
iter  40 value 89.438238
iter  50 value 87.460753
iter  60 value 87.458647
iter  70 value 84.377582
iter  80 value 83.168205
iter  90 value 82.657330
iter 100 value 82.635478
final  value 82.635478 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.772505 
final  value 94.054561 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.860954 
iter  10 value 94.058164
iter  20 value 93.340899
iter  30 value 91.255072
final  value 91.254786 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.628714 
iter  10 value 94.057699
iter  20 value 93.611569
iter  30 value 84.545800
iter  40 value 84.199708
iter  50 value 84.097295
final  value 84.097195 
converged
Fitting Repeat 3 

# weights:  305
initial  value 111.501830 
iter  10 value 94.058565
iter  20 value 93.981429
iter  30 value 88.634918
iter  40 value 88.627820
iter  50 value 88.624264
iter  60 value 88.624183
iter  70 value 88.623751
final  value 88.623651 
converged
Fitting Repeat 4 

# weights:  305
initial  value 99.138806 
iter  10 value 94.057846
iter  20 value 93.992101
iter  30 value 93.476581
iter  40 value 93.468935
final  value 93.468933 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.960113 
iter  10 value 94.057687
iter  20 value 93.175977
iter  30 value 84.104417
final  value 84.098479 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.644561 
iter  10 value 94.060733
iter  20 value 94.050261
final  value 93.474546 
converged
Fitting Repeat 2 

# weights:  507
initial  value 108.336815 
iter  10 value 91.218198
iter  20 value 82.008939
iter  30 value 82.008351
iter  40 value 81.841459
iter  50 value 79.558090
iter  60 value 79.539433
iter  70 value 79.539093
iter  80 value 79.458072
iter  90 value 78.782377
iter 100 value 76.729574
final  value 76.729574 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 94.304358 
iter  10 value 94.017907
iter  20 value 93.969624
iter  30 value 91.170541
iter  40 value 91.083660
iter  50 value 90.778548
iter  60 value 85.524270
iter  70 value 83.868193
iter  80 value 82.068006
iter  90 value 81.451237
iter 100 value 79.505162
final  value 79.505162 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.712403 
iter  10 value 89.035161
iter  20 value 87.168966
iter  30 value 87.163018
iter  40 value 87.020686
iter  50 value 85.592708
iter  60 value 85.490893
iter  70 value 85.490787
iter  80 value 85.490332
iter  90 value 85.413939
iter 100 value 84.375326
final  value 84.375326 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.106255 
iter  10 value 89.098801
iter  20 value 88.600912
iter  30 value 79.950690
iter  40 value 79.162767
iter  50 value 79.068418
iter  60 value 79.067619
iter  70 value 79.067110
iter  80 value 78.280847
final  value 78.270017 
converged
Fitting Repeat 1 

# weights:  103
initial  value 99.552247 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.536314 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.515133 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.868336 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.362891 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.564638 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 115.156458 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.867968 
final  value 94.461539 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.920004 
iter  10 value 94.354396
iter  10 value 94.354396
iter  10 value 94.354396
final  value 94.354396 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.090310 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.629188 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.969383 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.998740 
final  value 94.476471 
converged
Fitting Repeat 4 

# weights:  507
initial  value 126.126630 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 111.012685 
final  value 94.461539 
converged
Fitting Repeat 1 

# weights:  103
initial  value 101.751057 
iter  10 value 94.304652
iter  20 value 90.535504
iter  30 value 82.256854
iter  40 value 81.613214
iter  50 value 81.213434
iter  60 value 80.519317
iter  70 value 79.846047
iter  80 value 79.753262
final  value 79.753229 
converged
Fitting Repeat 2 

# weights:  103
initial  value 102.010659 
iter  10 value 94.503374
iter  20 value 93.516408
iter  30 value 85.476674
iter  40 value 84.158875
iter  50 value 82.501488
iter  60 value 81.912603
iter  70 value 81.827861
iter  80 value 81.760265
final  value 81.760255 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.175661 
iter  10 value 94.426423
iter  20 value 92.984860
iter  30 value 89.955567
iter  40 value 89.744912
iter  50 value 84.593353
iter  60 value 84.236569
iter  70 value 83.561539
iter  80 value 82.625556
iter  90 value 81.979638
final  value 81.979106 
converged
Fitting Repeat 4 

# weights:  103
initial  value 108.147451 
iter  10 value 93.337517
iter  20 value 85.761274
iter  30 value 85.238899
iter  40 value 84.487681
iter  50 value 82.546093
iter  60 value 80.013368
iter  70 value 79.930777
iter  80 value 79.927696
iter  80 value 79.927696
iter  80 value 79.927696
final  value 79.927696 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.261125 
iter  10 value 94.483281
iter  20 value 94.299241
iter  30 value 94.234606
iter  40 value 91.124947
iter  50 value 83.990061
iter  60 value 83.548838
iter  70 value 82.334097
iter  80 value 80.324237
iter  90 value 79.509525
iter 100 value 79.496289
final  value 79.496289 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 102.172013 
iter  10 value 95.144218
iter  20 value 94.511510
iter  30 value 87.407905
iter  40 value 85.773998
iter  50 value 82.453799
iter  60 value 81.958309
iter  70 value 81.634071
iter  80 value 81.469331
iter  90 value 81.360850
iter 100 value 79.887551
final  value 79.887551 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 110.787123 
iter  10 value 96.648993
iter  20 value 89.300019
iter  30 value 88.299991
iter  40 value 84.757582
iter  50 value 84.412540
iter  60 value 84.223604
iter  70 value 80.412334
iter  80 value 79.328929
iter  90 value 78.660980
iter 100 value 78.251641
final  value 78.251641 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.071573 
iter  10 value 91.085842
iter  20 value 86.723559
iter  30 value 86.233644
iter  40 value 86.083796
iter  50 value 86.010686
iter  60 value 85.603052
iter  70 value 82.922863
iter  80 value 81.555156
iter  90 value 81.052281
iter 100 value 80.563971
final  value 80.563971 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.270264 
iter  10 value 94.331769
iter  20 value 88.547781
iter  30 value 85.328084
iter  40 value 84.185072
iter  50 value 82.409130
iter  60 value 80.897037
iter  70 value 80.511906
iter  80 value 80.004076
iter  90 value 79.918112
iter 100 value 79.800892
final  value 79.800892 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 127.593062 
iter  10 value 94.247086
iter  20 value 93.872026
iter  30 value 87.167208
iter  40 value 83.484022
iter  50 value 82.909534
iter  60 value 82.248689
iter  70 value 81.824134
iter  80 value 80.816323
iter  90 value 79.691369
iter 100 value 79.517389
final  value 79.517389 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.967626 
iter  10 value 94.550489
iter  20 value 89.696427
iter  30 value 86.767309
iter  40 value 85.513173
iter  50 value 85.063708
iter  60 value 84.457362
iter  70 value 81.784135
iter  80 value 80.500045
iter  90 value 80.102929
iter 100 value 79.791894
final  value 79.791894 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.243952 
iter  10 value 101.020974
iter  20 value 90.233104
iter  30 value 84.492080
iter  40 value 83.891108
iter  50 value 82.552467
iter  60 value 82.270116
iter  70 value 82.168964
iter  80 value 82.012208
iter  90 value 81.697329
iter 100 value 80.429460
final  value 80.429460 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.402419 
iter  10 value 91.349077
iter  20 value 81.278258
iter  30 value 80.397392
iter  40 value 79.804150
iter  50 value 78.888366
iter  60 value 78.634006
iter  70 value 78.543336
iter  80 value 78.375289
iter  90 value 78.014310
iter 100 value 77.759409
final  value 77.759409 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 131.892510 
iter  10 value 94.529280
iter  20 value 93.712424
iter  30 value 89.013177
iter  40 value 83.146852
iter  50 value 81.054235
iter  60 value 79.578790
iter  70 value 78.715853
iter  80 value 78.567524
iter  90 value 78.374423
iter 100 value 78.041257
final  value 78.041257 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.463300 
iter  10 value 94.928709
iter  20 value 94.385816
iter  30 value 81.713385
iter  40 value 80.171442
iter  50 value 79.461442
iter  60 value 79.161758
iter  70 value 78.441352
iter  80 value 78.028599
iter  90 value 77.654753
iter 100 value 77.471999
final  value 77.471999 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.508812 
final  value 94.486068 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.854711 
final  value 94.485698 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.147625 
final  value 94.356229 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.057862 
final  value 94.355998 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.798297 
final  value 94.485859 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.038042 
iter  10 value 94.488731
iter  20 value 94.484235
iter  20 value 94.484235
final  value 94.484232 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.250730 
iter  10 value 94.489136
iter  20 value 94.484732
iter  30 value 94.484113
iter  40 value 94.440098
iter  50 value 84.154896
final  value 84.153800 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.354739 
iter  10 value 91.310360
iter  20 value 86.376337
iter  30 value 84.118109
iter  40 value 83.364895
iter  50 value 83.276053
iter  60 value 83.273968
iter  70 value 83.253099
iter  80 value 83.114537
iter  90 value 81.814785
iter 100 value 81.401327
final  value 81.401327 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 95.971329 
iter  10 value 94.454308
iter  20 value 94.440983
iter  30 value 86.369572
iter  40 value 86.358540
iter  50 value 85.970267
iter  60 value 82.532271
iter  70 value 80.974788
iter  80 value 79.933661
iter  90 value 79.651606
iter 100 value 79.641283
final  value 79.641283 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 99.967559 
iter  10 value 94.488773
iter  20 value 94.484285
iter  30 value 94.020554
iter  40 value 93.802804
iter  50 value 93.591750
iter  60 value 93.408548
iter  70 value 83.817020
iter  80 value 83.296524
iter  90 value 82.629897
iter 100 value 82.593816
final  value 82.593816 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.534766 
iter  10 value 94.313571
iter  20 value 94.047932
iter  30 value 88.672882
iter  40 value 83.742528
iter  50 value 83.623900
iter  60 value 81.869284
iter  70 value 80.883238
iter  80 value 80.858821
iter  90 value 80.834107
iter 100 value 80.672029
final  value 80.672029 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 118.468579 
iter  10 value 94.493199
iter  20 value 94.254109
iter  30 value 85.924645
iter  40 value 85.194760
iter  50 value 85.081447
iter  60 value 84.063850
iter  70 value 83.929785
iter  80 value 83.741339
iter  90 value 83.222311
iter 100 value 81.340914
final  value 81.340914 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 100.130047 
iter  10 value 94.378403
iter  20 value 94.361854
iter  30 value 93.711076
iter  40 value 93.576614
iter  50 value 93.575155
iter  60 value 93.574954
iter  70 value 93.574439
iter  80 value 93.573517
iter  90 value 93.486538
iter 100 value 93.486401
final  value 93.486401 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.949297 
iter  10 value 94.457065
iter  20 value 94.450162
iter  30 value 93.962591
iter  40 value 93.853857
iter  50 value 93.691008
iter  60 value 93.689345
iter  70 value 93.685902
iter  80 value 93.554627
iter  90 value 92.230081
iter 100 value 92.176578
final  value 92.176578 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 101.543667 
iter  10 value 94.335249
iter  20 value 94.292641
iter  30 value 93.831537
iter  40 value 84.678456
iter  50 value 83.973087
iter  60 value 83.961060
final  value 83.961052 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.685108 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.848440 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.407750 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.984990 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.047829 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.202975 
iter  10 value 93.710742
final  value 93.701656 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.764384 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.464578 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 107.552623 
iter  10 value 85.274422
iter  20 value 85.061140
iter  30 value 84.504562
final  value 84.504556 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.572049 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 127.400408 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 101.591511 
final  value 94.466106 
converged
Fitting Repeat 3 

# weights:  507
initial  value 97.493346 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 94.910077 
iter  10 value 86.196063
iter  20 value 85.925313
iter  30 value 85.624602
iter  40 value 84.072595
iter  50 value 83.682945
iter  60 value 83.672562
iter  70 value 83.468322
final  value 83.468175 
converged
Fitting Repeat 5 

# weights:  507
initial  value 98.399714 
final  value 94.467391 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.562632 
iter  10 value 94.497190
iter  20 value 94.338781
iter  30 value 93.944475
iter  40 value 93.791791
iter  50 value 92.782132
iter  60 value 92.104275
iter  70 value 89.726189
iter  80 value 88.898788
iter  90 value 85.926759
iter 100 value 84.906742
final  value 84.906742 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 96.877298 
iter  10 value 94.473521
iter  20 value 90.854557
iter  30 value 88.749971
iter  40 value 86.515752
iter  50 value 85.545374
iter  60 value 85.401350
iter  70 value 85.245488
iter  80 value 85.173436
final  value 85.173133 
converged
Fitting Repeat 3 

# weights:  103
initial  value 104.351178 
iter  10 value 94.289786
iter  20 value 88.232146
iter  30 value 86.883978
iter  40 value 86.369161
iter  50 value 85.970732
iter  60 value 85.466181
iter  70 value 84.460482
iter  80 value 84.172057
final  value 84.171358 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.335189 
iter  10 value 94.397736
iter  20 value 89.582247
iter  30 value 89.206634
iter  40 value 85.589468
iter  50 value 85.305161
iter  60 value 85.186709
iter  70 value 85.173133
iter  70 value 85.173133
iter  70 value 85.173133
final  value 85.173133 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.126330 
iter  10 value 94.257387
iter  20 value 87.943175
iter  30 value 86.256329
iter  40 value 85.197126
iter  50 value 84.797046
iter  60 value 84.559369
final  value 84.543453 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.092281 
iter  10 value 94.350555
iter  20 value 86.439660
iter  30 value 86.160683
iter  40 value 85.934253
iter  50 value 85.371182
iter  60 value 84.457960
iter  70 value 83.914063
iter  80 value 83.539346
iter  90 value 83.286681
iter 100 value 83.244164
final  value 83.244164 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 109.835754 
iter  10 value 91.153084
iter  20 value 85.417219
iter  30 value 84.338047
iter  40 value 83.475879
iter  50 value 82.523980
iter  60 value 82.315288
iter  70 value 82.299903
iter  80 value 82.294242
iter  90 value 82.151101
iter 100 value 81.930344
final  value 81.930344 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.587806 
iter  10 value 94.360372
iter  20 value 86.862762
iter  30 value 86.549876
iter  40 value 84.750799
iter  50 value 82.986664
iter  60 value 82.012917
iter  70 value 81.663985
iter  80 value 81.246718
iter  90 value 80.956230
iter 100 value 80.870278
final  value 80.870278 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 145.800067 
iter  10 value 94.901865
iter  20 value 94.501157
iter  30 value 94.312520
iter  40 value 93.117612
iter  50 value 90.111198
iter  60 value 88.397136
iter  70 value 85.291204
iter  80 value 85.115854
iter  90 value 84.961660
iter 100 value 84.908203
final  value 84.908203 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 101.378139 
iter  10 value 94.323979
iter  20 value 91.359174
iter  30 value 87.924458
iter  40 value 87.223685
iter  50 value 85.342219
iter  60 value 84.975877
iter  70 value 84.938609
iter  80 value 84.921368
iter  90 value 84.580055
iter 100 value 84.176152
final  value 84.176152 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.346919 
iter  10 value 94.521732
iter  20 value 94.356805
iter  30 value 92.123607
iter  40 value 86.395814
iter  50 value 83.747709
iter  60 value 82.738265
iter  70 value 81.826134
iter  80 value 81.775568
iter  90 value 81.712351
iter 100 value 81.467270
final  value 81.467270 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 106.177135 
iter  10 value 94.559562
iter  20 value 90.430139
iter  30 value 87.206731
iter  40 value 85.082391
iter  50 value 82.041194
iter  60 value 81.525072
iter  70 value 81.200982
iter  80 value 81.109741
iter  90 value 81.019866
iter 100 value 81.004805
final  value 81.004805 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.874568 
iter  10 value 94.448389
iter  20 value 92.030780
iter  30 value 86.655849
iter  40 value 85.397409
iter  50 value 85.045434
iter  60 value 84.866520
iter  70 value 83.559577
iter  80 value 82.533354
iter  90 value 82.312569
iter 100 value 81.915585
final  value 81.915585 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 106.170960 
iter  10 value 89.463858
iter  20 value 85.656968
iter  30 value 84.858968
iter  40 value 82.629573
iter  50 value 82.380190
iter  60 value 81.878981
iter  70 value 81.490347
iter  80 value 81.220974
iter  90 value 81.030439
iter 100 value 81.006578
final  value 81.006578 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.651940 
iter  10 value 95.356349
iter  20 value 93.576280
iter  30 value 87.502074
iter  40 value 85.955139
iter  50 value 85.087022
iter  60 value 84.659209
iter  70 value 83.771578
iter  80 value 83.237468
iter  90 value 82.729168
iter 100 value 82.434060
final  value 82.434060 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 102.487337 
final  value 94.485817 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.837539 
final  value 94.469125 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.776718 
final  value 94.485885 
converged
Fitting Repeat 4 

# weights:  103
initial  value 111.127446 
iter  10 value 94.469103
iter  20 value 94.466926
iter  30 value 91.065497
iter  40 value 88.581112
iter  50 value 87.329263
iter  60 value 87.310374
iter  70 value 87.287904
iter  80 value 87.276077
iter  90 value 87.275365
iter 100 value 87.273329
final  value 87.273329 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 101.439610 
final  value 94.485674 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.192003 
iter  10 value 94.488640
iter  20 value 94.439460
iter  30 value 91.952471
iter  30 value 91.952471
final  value 91.952464 
converged
Fitting Repeat 2 

# weights:  305
initial  value 110.391460 
iter  10 value 94.488757
iter  20 value 94.476163
iter  30 value 87.725018
iter  40 value 85.710256
iter  50 value 85.680843
iter  60 value 85.680054
iter  70 value 85.539489
final  value 85.539005 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.546843 
iter  10 value 94.488983
iter  20 value 94.394679
iter  30 value 92.839577
iter  40 value 86.282194
iter  50 value 85.624911
iter  60 value 84.965543
iter  70 value 84.305100
iter  80 value 84.299304
final  value 84.299272 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.930397 
iter  10 value 94.472711
iter  20 value 94.467880
final  value 94.467470 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.347513 
iter  10 value 94.471935
iter  20 value 93.522566
iter  30 value 90.442101
iter  40 value 85.825250
iter  50 value 84.308630
iter  60 value 84.224446
final  value 84.223484 
converged
Fitting Repeat 1 

# weights:  507
initial  value 134.931260 
iter  10 value 94.492784
iter  20 value 94.485022
iter  30 value 94.440451
iter  40 value 93.709347
iter  40 value 93.709346
iter  50 value 93.228873
iter  60 value 93.217408
final  value 93.217356 
converged
Fitting Repeat 2 

# weights:  507
initial  value 112.987390 
iter  10 value 94.492793
iter  20 value 94.384018
iter  30 value 92.883273
iter  40 value 92.882652
iter  50 value 92.882390
iter  60 value 92.838047
final  value 92.834275 
converged
Fitting Repeat 3 

# weights:  507
initial  value 110.879725 
iter  10 value 94.493893
iter  20 value 94.482324
iter  30 value 94.480785
iter  40 value 94.455913
final  value 94.455879 
converged
Fitting Repeat 4 

# weights:  507
initial  value 112.784770 
iter  10 value 94.476234
iter  20 value 94.468943
final  value 94.468661 
converged
Fitting Repeat 5 

# weights:  507
initial  value 106.218972 
iter  10 value 94.288167
iter  20 value 92.863668
iter  30 value 92.820033
iter  40 value 92.780890
iter  50 value 92.775141
iter  60 value 88.628712
iter  70 value 86.227822
iter  80 value 86.113848
final  value 86.113435 
converged
Fitting Repeat 1 

# weights:  103
initial  value 105.961416 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 100.183589 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.028205 
iter  10 value 89.458557
final  value 88.643641 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.050815 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.766985 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.029831 
final  value 94.466823 
converged
Fitting Repeat 2 

# weights:  305
initial  value 106.590107 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.061975 
final  value 94.275362 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.973157 
iter  10 value 93.050330
iter  20 value 87.250658
iter  30 value 87.221258
iter  40 value 86.007533
final  value 85.801475 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.044030 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.823758 
iter  10 value 93.788904
iter  20 value 93.673869
final  value 93.673806 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.373484 
final  value 94.322897 
converged
Fitting Repeat 3 

# weights:  507
initial  value 112.561438 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.030756 
iter  10 value 94.083680
final  value 94.083670 
converged
Fitting Repeat 5 

# weights:  507
initial  value 94.980705 
iter  10 value 91.788154
iter  20 value 90.518789
iter  30 value 90.512942
final  value 90.512619 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.756549 
iter  10 value 94.495526
iter  20 value 94.421999
iter  30 value 94.332811
iter  40 value 94.329885
iter  50 value 93.978952
iter  60 value 87.236536
iter  70 value 87.082325
iter  80 value 86.726763
iter  90 value 85.858990
iter 100 value 85.293390
final  value 85.293390 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.670570 
iter  10 value 94.488563
iter  20 value 92.242831
iter  30 value 83.463080
iter  40 value 83.310262
iter  50 value 82.333866
iter  60 value 80.723710
iter  70 value 80.335010
iter  80 value 79.931834
final  value 79.923716 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.419439 
iter  10 value 94.154906
iter  20 value 88.491056
iter  30 value 87.110230
iter  40 value 86.989761
iter  50 value 86.756210
iter  60 value 86.134983
iter  70 value 85.302363
iter  80 value 85.243956
iter  80 value 85.243955
iter  80 value 85.243955
final  value 85.243955 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.144290 
iter  10 value 94.486955
iter  20 value 91.835620
iter  30 value 91.251253
iter  40 value 91.167385
iter  50 value 91.161892
iter  60 value 91.159679
iter  70 value 91.141367
iter  80 value 87.894524
iter  90 value 87.727557
iter 100 value 86.263397
final  value 86.263397 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 96.698185 
iter  10 value 94.491041
iter  20 value 93.495204
iter  30 value 88.400997
iter  40 value 84.624318
iter  50 value 81.627187
iter  60 value 80.806462
iter  70 value 80.547044
iter  80 value 80.159557
iter  90 value 80.083676
iter 100 value 79.950997
final  value 79.950997 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.319899 
iter  10 value 94.611990
iter  20 value 94.489412
iter  30 value 93.801199
iter  40 value 87.652504
iter  50 value 87.280796
iter  60 value 86.694050
iter  70 value 85.776237
iter  80 value 81.876033
iter  90 value 80.326620
iter 100 value 79.630511
final  value 79.630511 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.454821 
iter  10 value 94.715112
iter  20 value 88.743993
iter  30 value 87.300122
iter  40 value 84.630386
iter  50 value 83.325474
iter  60 value 82.284368
iter  70 value 82.029915
iter  80 value 81.990915
iter  90 value 81.572328
iter 100 value 81.395609
final  value 81.395609 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 99.980485 
iter  10 value 94.239735
iter  20 value 87.522702
iter  30 value 82.827541
iter  40 value 80.119055
iter  50 value 79.321942
iter  60 value 79.209421
iter  70 value 79.206901
iter  80 value 79.195326
iter  90 value 79.161632
iter 100 value 78.949084
final  value 78.949084 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 118.441580 
iter  10 value 94.146951
iter  20 value 93.820099
iter  30 value 90.502912
iter  40 value 87.558464
iter  50 value 83.815165
iter  60 value 83.006275
iter  70 value 81.273726
iter  80 value 80.856361
iter  90 value 80.132927
iter 100 value 79.443449
final  value 79.443449 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 112.398558 
iter  10 value 89.475448
iter  20 value 87.299793
iter  30 value 84.254522
iter  40 value 82.415626
iter  50 value 81.976035
iter  60 value 80.782506
iter  70 value 80.451987
iter  80 value 79.919575
iter  90 value 79.517545
iter 100 value 79.422099
final  value 79.422099 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 120.784950 
iter  10 value 94.899488
iter  20 value 94.515404
iter  30 value 93.775095
iter  40 value 90.877032
iter  50 value 87.061766
iter  60 value 86.135969
iter  70 value 85.916708
iter  80 value 83.142191
iter  90 value 80.035945
iter 100 value 79.407272
final  value 79.407272 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.024885 
iter  10 value 94.795816
iter  20 value 94.468211
iter  30 value 91.124500
iter  40 value 89.298803
iter  50 value 86.611497
iter  60 value 82.170929
iter  70 value 80.955326
iter  80 value 80.045256
iter  90 value 79.200336
iter 100 value 78.945802
final  value 78.945802 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 126.485413 
iter  10 value 95.285019
iter  20 value 92.122159
iter  30 value 89.812623
iter  40 value 83.164601
iter  50 value 80.269273
iter  60 value 79.768391
iter  70 value 79.543196
iter  80 value 79.188503
iter  90 value 78.998588
iter 100 value 78.967506
final  value 78.967506 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.414151 
iter  10 value 94.500488
iter  20 value 86.749325
iter  30 value 86.020121
iter  40 value 84.361036
iter  50 value 83.559048
iter  60 value 81.771997
iter  70 value 80.743091
iter  80 value 80.635256
iter  90 value 80.349981
iter 100 value 80.051052
final  value 80.051052 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.042383 
iter  10 value 94.130013
iter  20 value 89.534867
iter  30 value 88.173440
iter  40 value 86.655447
iter  50 value 83.448663
iter  60 value 81.024723
iter  70 value 79.301577
iter  80 value 78.701070
iter  90 value 78.557456
iter 100 value 78.446203
final  value 78.446203 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.180647 
iter  10 value 94.485709
iter  20 value 94.484228
final  value 94.484225 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.011344 
final  value 94.277023 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.517020 
final  value 94.485386 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.641671 
final  value 94.485841 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.600103 
final  value 94.485846 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.215253 
iter  10 value 94.488926
iter  20 value 94.423386
iter  30 value 86.986613
iter  40 value 86.764873
iter  50 value 85.375143
iter  60 value 84.301156
iter  70 value 81.183695
iter  80 value 80.095648
iter  90 value 80.092212
iter 100 value 80.088973
final  value 80.088973 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 96.420255 
iter  10 value 94.488386
iter  20 value 93.591953
iter  30 value 91.177779
iter  40 value 91.165345
iter  50 value 90.743923
iter  60 value 89.745332
iter  70 value 89.744030
iter  80 value 89.743801
iter  90 value 86.406711
iter 100 value 84.718373
final  value 84.718373 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 119.506666 
iter  10 value 94.489136
iter  20 value 94.484428
iter  30 value 91.819871
iter  40 value 88.173048
iter  50 value 88.043690
iter  60 value 86.829334
iter  70 value 86.597528
iter  80 value 86.590839
iter  90 value 86.582217
iter 100 value 86.298413
final  value 86.298413 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 102.051187 
iter  10 value 94.489273
iter  20 value 94.482733
iter  30 value 86.562615
iter  40 value 83.843955
iter  50 value 83.151621
iter  60 value 82.698292
iter  70 value 82.692021
iter  80 value 82.632148
iter  90 value 82.626105
iter 100 value 82.115412
final  value 82.115412 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 106.487864 
iter  10 value 93.793536
iter  20 value 93.766003
iter  30 value 86.184958
iter  40 value 84.419890
iter  50 value 84.419142
iter  60 value 84.418893
iter  70 value 84.418736
iter  80 value 84.009002
iter  90 value 81.622390
iter 100 value 81.501124
final  value 81.501124 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 106.858964 
iter  10 value 94.492289
iter  20 value 94.487239
iter  30 value 89.007707
iter  40 value 88.118490
iter  50 value 84.117120
iter  60 value 83.922615
iter  70 value 83.910319
iter  80 value 83.902580
iter  90 value 80.260925
iter 100 value 78.190568
final  value 78.190568 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 100.332624 
iter  10 value 93.957593
iter  20 value 86.606260
iter  30 value 86.069191
final  value 86.067306 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.901083 
iter  10 value 94.489282
iter  20 value 94.352572
iter  30 value 86.712568
iter  40 value 86.707572
iter  50 value 86.691666
iter  50 value 86.691666
final  value 86.691666 
converged
Fitting Repeat 4 

# weights:  507
initial  value 113.594749 
iter  10 value 94.475131
iter  20 value 94.372461
iter  30 value 86.537460
iter  40 value 84.791729
iter  50 value 84.223351
iter  60 value 82.224797
iter  70 value 82.130324
iter  80 value 82.079789
iter  90 value 82.076265
iter 100 value 80.477143
final  value 80.477143 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.729355 
iter  10 value 94.475233
iter  20 value 94.469701
iter  30 value 94.468401
iter  40 value 94.263404
iter  50 value 90.355137
iter  60 value 89.355428
iter  70 value 89.316200
iter  80 value 86.651154
iter  90 value 84.852682
iter 100 value 84.091634
final  value 84.091634 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 143.543175 
iter  10 value 118.654488
iter  20 value 117.899111
iter  30 value 117.190390
iter  40 value 115.003316
iter  50 value 109.555868
iter  60 value 106.765116
iter  70 value 104.466036
iter  80 value 103.256186
iter  90 value 102.590821
iter 100 value 101.849755
final  value 101.849755 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 135.637157 
iter  10 value 117.823971
iter  20 value 117.573416
iter  30 value 109.750054
iter  40 value 109.017526
iter  50 value 108.291280
iter  60 value 103.883471
iter  70 value 102.489284
iter  80 value 101.752330
iter  90 value 101.335871
iter 100 value 101.227356
final  value 101.227356 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 149.801209 
iter  10 value 117.902785
iter  20 value 109.463109
iter  30 value 107.714671
iter  40 value 106.665457
iter  50 value 103.863616
iter  60 value 102.985049
iter  70 value 102.145271
iter  80 value 101.855619
iter  90 value 101.534464
iter 100 value 100.999712
final  value 100.999712 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 127.208476 
iter  10 value 118.012894
iter  20 value 114.877704
iter  30 value 109.800396
iter  40 value 108.577400
iter  50 value 104.245263
iter  60 value 103.598603
iter  70 value 103.079888
iter  80 value 102.854724
iter  90 value 102.576006
iter 100 value 102.224847
final  value 102.224847 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 143.253915 
iter  10 value 118.229911
iter  20 value 116.849025
iter  30 value 115.332896
iter  40 value 111.808988
iter  50 value 107.243464
iter  60 value 104.014766
iter  70 value 103.199294
iter  80 value 102.955162
iter  90 value 102.401755
iter 100 value 101.207172
final  value 101.207172 
stopped after 100 iterations
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases


RUNIT TEST PROTOCOL -- Sat May  4 08:35:07 2024 
*********************************************** 
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 
 56.073   1.576  82.944 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod38.281 0.60338.979
FreqInteractors0.2730.0240.298
calculateAAC0.0420.0080.049
calculateAutocor0.7230.0160.743
calculateCTDC0.0930.0000.094
calculateCTDD0.7760.0000.777
calculateCTDT0.2700.0040.274
calculateCTriad0.4710.0120.483
calculateDC0.1270.0040.131
calculateF0.4610.0230.487
calculateKSAAP0.1450.0010.145
calculateQD_Sm2.4390.0042.447
calculateTC2.4250.0192.450
calculateTC_Sm0.3880.0000.389
corr_plot38.315 0.46738.856
enrichfindP 0.537 0.02839.625
enrichfind_hp0.0970.0042.177
enrichplot0.4780.0560.536
filter_missing_values0.0010.0000.002
getFASTA0.0940.0008.377
getHPI0.0010.0000.001
get_negativePPI0.0020.0000.001
get_positivePPI000
impute_missing_data0.0020.0000.001
plotPPI0.0810.0080.089
pred_ensembel18.408 0.55316.580
var_imp38.610 0.87939.559