Back to Multiple platform build/check report for BioC 3.19:   simplified   long
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This page was generated on 2024-05-04 11:36:40 -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 nebbiolo1


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.

raw results


Summary

Package: HPiP
Version: 1.10.0
Command: /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --timings HPiP_1.10.0.tar.gz
StartedAt: 2024-05-04 00:08:57 -0400 (Sat, 04 May 2024)
EndedAt: 2024-05-04 00:22:40 -0400 (Sat, 04 May 2024)
EllapsedTime: 822.5 seconds
RetCode: 0
Status:   OK  
CheckDir: HPiP.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   /home/biocbuild/bbs-3.19-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.19-bioc/R/site-library --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: x86_64-pc-linux-gnu
* R was compiled by
    gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
    GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* 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       36.442  0.931  37.374
FSmethod      34.787  0.653  35.439
corr_plot     34.502  0.296  34.799
pred_ensembel 13.473  0.657  10.880
enrichfindP    0.458  0.042  12.046
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘runTests.R’
 OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE

Status: 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/bbs-3.19-bioc/R/bin/R CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library ‘/home/biocbuild/bbs-3.19-bioc/R/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: x86_64-pc-linux-gnu

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1 

# weights:  103
initial  value 97.785550 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.315168 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.150639 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 102.856934 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.189374 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.821412 
iter  10 value 92.147252
iter  20 value 91.348044
iter  30 value 90.414313
final  value 90.234101 
converged
Fitting Repeat 2 

# weights:  305
initial  value 119.617973 
iter  10 value 94.466823
iter  10 value 94.466823
iter  10 value 94.466823
final  value 94.466823 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.489970 
iter  10 value 93.448109
iter  20 value 88.949584
iter  30 value 88.709498
final  value 88.707699 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.686729 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.673333 
iter  10 value 94.169911
iter  20 value 93.735989
final  value 93.735903 
converged
Fitting Repeat 1 

# weights:  507
initial  value 120.224303 
iter  10 value 93.116790
final  value 93.102857 
converged
Fitting Repeat 2 

# weights:  507
initial  value 146.036678 
iter  10 value 93.797016
iter  20 value 93.617120
final  value 93.617022 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.941142 
iter  10 value 93.520342
final  value 80.136336 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.764792 
final  value 94.466822 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.146697 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  103
initial  value 103.448403 
iter  10 value 94.431357
iter  20 value 85.373597
iter  30 value 81.959253
iter  40 value 80.240221
iter  50 value 79.564039
iter  60 value 79.140229
iter  70 value 78.763194
iter  80 value 78.069938
iter  90 value 77.549743
iter 100 value 77.546502
final  value 77.546502 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 103.183432 
iter  10 value 94.489612
iter  20 value 93.381886
iter  30 value 82.314957
iter  40 value 81.957744
iter  50 value 81.357797
iter  60 value 81.230683
iter  70 value 81.036882
iter  80 value 81.007647
final  value 81.005617 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.120577 
iter  10 value 94.487397
iter  20 value 94.335367
iter  30 value 93.733077
iter  40 value 85.293805
iter  50 value 85.011067
iter  60 value 83.791461
iter  70 value 81.667835
iter  80 value 81.155180
iter  90 value 80.987065
iter 100 value 80.971014
final  value 80.971014 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.388691 
iter  10 value 91.925520
iter  20 value 85.545368
iter  30 value 84.499235
iter  40 value 82.077470
iter  50 value 81.604144
iter  60 value 81.329741
iter  70 value 81.120575
iter  80 value 81.008181
final  value 81.005618 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.360838 
iter  10 value 94.488113
iter  20 value 87.221410
iter  30 value 83.170061
iter  40 value 82.881753
iter  50 value 81.151684
iter  60 value 81.025794
iter  70 value 81.005623
final  value 81.005617 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.037879 
iter  10 value 94.366347
iter  20 value 91.473790
iter  30 value 86.719406
iter  40 value 86.122587
iter  50 value 83.541801
iter  60 value 81.413388
iter  70 value 80.500824
iter  80 value 80.288277
iter  90 value 80.150185
iter 100 value 80.096014
final  value 80.096014 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.133080 
iter  10 value 93.591824
iter  20 value 85.995978
iter  30 value 85.242523
iter  40 value 83.706811
iter  50 value 83.145737
iter  60 value 79.557900
iter  70 value 78.373171
iter  80 value 77.821422
iter  90 value 77.121924
iter 100 value 76.705504
final  value 76.705504 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.625416 
iter  10 value 94.486819
iter  20 value 93.745033
iter  30 value 91.571718
iter  40 value 81.843704
iter  50 value 80.885675
iter  60 value 80.540167
iter  70 value 79.455783
iter  80 value 79.416575
iter  90 value 79.139260
iter 100 value 78.284915
final  value 78.284915 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.215796 
iter  10 value 94.698193
iter  20 value 89.547312
iter  30 value 82.597336
iter  40 value 81.364016
iter  50 value 81.059062
iter  60 value 80.821366
iter  70 value 80.143442
iter  80 value 77.895180
iter  90 value 77.739205
iter 100 value 77.449166
final  value 77.449166 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 117.260495 
iter  10 value 97.163425
iter  20 value 92.599725
iter  30 value 84.534935
iter  40 value 82.133142
iter  50 value 78.602173
iter  60 value 76.786270
iter  70 value 76.622975
iter  80 value 76.405343
iter  90 value 76.161409
iter 100 value 75.835399
final  value 75.835399 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.059618 
iter  10 value 94.839184
iter  20 value 85.054761
iter  30 value 84.358135
iter  40 value 79.829625
iter  50 value 77.949367
iter  60 value 77.681817
iter  70 value 76.835169
iter  80 value 76.560161
iter  90 value 75.968045
iter 100 value 75.637860
final  value 75.637860 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 133.085540 
iter  10 value 95.539242
iter  20 value 86.264761
iter  30 value 82.715461
iter  40 value 81.445114
iter  50 value 80.755209
iter  60 value 80.721832
iter  70 value 80.535699
iter  80 value 79.867647
iter  90 value 78.135269
iter 100 value 76.999419
final  value 76.999419 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 103.466910 
iter  10 value 95.039437
iter  20 value 94.300138
iter  30 value 92.680945
iter  40 value 86.176399
iter  50 value 82.829291
iter  60 value 82.580260
iter  70 value 80.454820
iter  80 value 78.859868
iter  90 value 77.870797
iter 100 value 77.600703
final  value 77.600703 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 112.590008 
iter  10 value 94.507475
iter  20 value 94.333671
iter  30 value 88.086426
iter  40 value 81.330555
iter  50 value 79.427353
iter  60 value 78.609831
iter  70 value 78.071651
iter  80 value 76.903512
iter  90 value 76.397327
iter 100 value 75.977227
final  value 75.977227 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 114.526986 
iter  10 value 94.659693
iter  20 value 92.428777
iter  30 value 90.478896
iter  40 value 86.615964
iter  50 value 86.193897
iter  60 value 85.099786
iter  70 value 84.772302
iter  80 value 82.988539
iter  90 value 81.446024
iter 100 value 80.613914
final  value 80.613914 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.363143 
iter  10 value 92.403813
iter  20 value 91.571470
iter  30 value 91.571296
iter  40 value 85.857015
iter  50 value 82.735246
iter  60 value 82.630481
iter  70 value 81.913012
iter  80 value 81.761113
iter  90 value 81.760568
iter 100 value 81.757263
final  value 81.757263 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 97.129008 
iter  10 value 94.468496
iter  20 value 87.058903
iter  30 value 86.111364
iter  40 value 86.052766
iter  50 value 84.271255
iter  60 value 84.232094
iter  70 value 84.135985
iter  80 value 83.990737
iter  90 value 83.990408
iter 100 value 83.989685
final  value 83.989685 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 102.566134 
final  value 94.485899 
converged
Fitting Repeat 4 

# weights:  103
initial  value 107.581571 
final  value 94.485683 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.434140 
final  value 94.485806 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.380857 
iter  10 value 92.681854
iter  20 value 90.158672
iter  30 value 90.156972
iter  40 value 90.154960
iter  50 value 90.131970
iter  60 value 90.033554
iter  70 value 88.851647
iter  80 value 88.844324
final  value 88.844208 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.256318 
iter  10 value 94.471492
iter  20 value 94.467208
iter  30 value 84.862729
iter  40 value 82.462673
iter  50 value 82.278037
iter  60 value 80.652919
iter  70 value 79.825408
iter  80 value 79.818836
iter  90 value 79.818576
iter  90 value 79.818576
iter  90 value 79.818576
final  value 79.818576 
converged
Fitting Repeat 3 

# weights:  305
initial  value 99.675378 
iter  10 value 94.471576
iter  20 value 94.413788
iter  30 value 80.170903
iter  40 value 80.130966
iter  50 value 80.111388
iter  60 value 79.959128
iter  70 value 79.767651
iter  80 value 79.765284
iter  90 value 79.765245
iter  90 value 79.765245
iter  90 value 79.765245
final  value 79.765245 
converged
Fitting Repeat 4 

# weights:  305
initial  value 104.168852 
iter  10 value 94.489435
iter  20 value 94.453502
iter  30 value 87.917286
iter  40 value 87.847657
iter  50 value 87.584327
iter  60 value 85.346330
iter  70 value 83.471701
iter  80 value 82.890971
final  value 82.851504 
converged
Fitting Repeat 5 

# weights:  305
initial  value 106.226632 
iter  10 value 94.471894
iter  20 value 94.440376
iter  30 value 89.592567
final  value 89.074009 
converged
Fitting Repeat 1 

# weights:  507
initial  value 97.228215 
iter  10 value 85.187923
iter  20 value 84.641230
iter  30 value 79.842741
iter  40 value 79.825852
iter  50 value 79.818794
iter  60 value 79.569069
iter  70 value 76.115604
iter  80 value 75.136818
iter  90 value 75.115890
iter 100 value 75.019534
final  value 75.019534 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 107.592095 
iter  10 value 94.474497
iter  20 value 85.600721
iter  30 value 82.220119
final  value 82.216438 
converged
Fitting Repeat 3 

# weights:  507
initial  value 113.704618 
iter  10 value 94.452086
iter  20 value 94.448281
iter  30 value 94.300089
iter  40 value 93.603236
iter  50 value 86.549498
iter  60 value 86.250642
iter  70 value 86.246549
iter  80 value 86.245213
iter  90 value 85.580774
iter 100 value 85.116689
final  value 85.116689 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.108126 
iter  10 value 94.247105
iter  20 value 94.236848
iter  30 value 92.851943
iter  40 value 89.958128
iter  50 value 89.613106
iter  60 value 89.515133
iter  70 value 89.511907
iter  80 value 89.510579
iter  90 value 86.007562
iter 100 value 84.543545
final  value 84.543545 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.121714 
iter  10 value 94.474757
iter  20 value 93.693595
iter  30 value 85.565291
iter  40 value 84.897094
iter  50 value 84.749199
iter  60 value 84.746907
final  value 84.746855 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.160778 
final  value 93.320225 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.691568 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.593595 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.489879 
iter  10 value 94.112904
iter  10 value 94.112904
iter  10 value 94.112904
final  value 94.112904 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.337938 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 105.003465 
iter  10 value 94.484211
iter  10 value 94.484211
iter  10 value 94.484211
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 100.063536 
iter  10 value 94.112904
iter  10 value 94.112904
iter  10 value 94.112904
final  value 94.112904 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.512336 
iter  10 value 85.831948
iter  20 value 81.159190
iter  30 value 80.762929
iter  40 value 80.718975
iter  50 value 80.710866
final  value 80.704738 
converged
Fitting Repeat 4 

# weights:  305
initial  value 108.651631 
iter  10 value 94.112905
final  value 94.112903 
converged
Fitting Repeat 5 

# weights:  305
initial  value 111.994434 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.574464 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.194561 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 100.059120 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 107.870183 
iter  10 value 94.112905
final  value 94.112903 
converged
Fitting Repeat 5 

# weights:  507
initial  value 109.414917 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 106.319402 
iter  10 value 94.586269
iter  20 value 94.488593
iter  30 value 92.205706
iter  40 value 91.056543
iter  50 value 83.183886
iter  60 value 81.653465
iter  70 value 80.980888
iter  80 value 79.602143
iter  90 value 79.211525
iter 100 value 78.430181
final  value 78.430181 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 102.312853 
iter  10 value 94.482279
iter  20 value 83.691499
iter  30 value 80.473690
iter  40 value 79.712877
iter  50 value 79.312878
iter  60 value 79.205483
iter  70 value 78.464320
iter  80 value 78.405889
iter  90 value 78.401434
final  value 78.401428 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.696187 
iter  10 value 94.489007
iter  20 value 93.807034
iter  30 value 93.176625
iter  40 value 93.007945
iter  50 value 92.991211
iter  60 value 86.663501
iter  70 value 84.665459
iter  80 value 82.163170
iter  90 value 81.862869
iter 100 value 81.850943
final  value 81.850943 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.897536 
iter  10 value 94.470860
iter  20 value 85.312127
iter  30 value 81.505605
iter  40 value 80.522063
iter  50 value 79.787008
iter  60 value 79.516481
iter  70 value 79.255580
iter  80 value 79.140862
iter  90 value 78.577826
iter 100 value 78.402304
final  value 78.402304 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.866486 
iter  10 value 94.275995
iter  20 value 93.008652
iter  30 value 91.838446
iter  40 value 85.698252
iter  50 value 84.834460
iter  60 value 83.222017
iter  70 value 81.572581
iter  80 value 81.323805
iter  90 value 81.282050
iter 100 value 81.281261
final  value 81.281261 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 101.430831 
iter  10 value 93.770342
iter  20 value 82.713802
iter  30 value 81.854046
iter  40 value 81.152570
iter  50 value 80.903387
iter  60 value 80.650135
iter  70 value 80.096209
iter  80 value 79.567005
iter  90 value 78.568506
iter 100 value 77.861383
final  value 77.861383 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.357895 
iter  10 value 93.788755
iter  20 value 82.703296
iter  30 value 80.795400
iter  40 value 79.651705
iter  50 value 79.209622
iter  60 value 77.790759
iter  70 value 77.417874
iter  80 value 77.386545
iter  90 value 77.380900
iter 100 value 77.378816
final  value 77.378816 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 112.812234 
iter  10 value 95.188084
iter  20 value 94.077472
iter  30 value 90.436160
iter  40 value 83.960815
iter  50 value 83.569357
iter  60 value 83.124716
iter  70 value 81.437982
iter  80 value 79.575722
iter  90 value 77.965676
iter 100 value 77.562016
final  value 77.562016 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.393380 
iter  10 value 92.830050
iter  20 value 85.547370
iter  30 value 82.449015
iter  40 value 79.907101
iter  50 value 78.521772
iter  60 value 77.964194
iter  70 value 77.756956
iter  80 value 77.706299
iter  90 value 77.672074
iter 100 value 77.659742
final  value 77.659742 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.833937 
iter  10 value 94.379826
iter  20 value 92.754077
iter  30 value 82.735681
iter  40 value 82.692041
iter  50 value 82.327174
iter  60 value 80.327473
iter  70 value 78.681386
iter  80 value 78.110458
iter  90 value 78.028026
iter 100 value 77.998812
final  value 77.998812 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 122.952161 
iter  10 value 94.587211
iter  20 value 92.688448
iter  30 value 90.378000
iter  40 value 88.510202
iter  50 value 83.800953
iter  60 value 81.573799
iter  70 value 80.742176
iter  80 value 79.600307
iter  90 value 77.986169
iter 100 value 77.694169
final  value 77.694169 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.640142 
iter  10 value 92.865506
iter  20 value 89.523915
iter  30 value 83.955426
iter  40 value 81.100001
iter  50 value 80.221582
iter  60 value 79.035273
iter  70 value 77.854108
iter  80 value 76.969130
iter  90 value 76.759562
iter 100 value 76.634138
final  value 76.634138 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 135.083880 
iter  10 value 94.217388
iter  20 value 89.201749
iter  30 value 82.395537
iter  40 value 81.864916
iter  50 value 81.244247
iter  60 value 79.675327
iter  70 value 78.708476
iter  80 value 78.174215
iter  90 value 77.798799
iter 100 value 77.714466
final  value 77.714466 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 111.157647 
iter  10 value 93.014435
iter  20 value 90.126028
iter  30 value 84.237417
iter  40 value 80.003251
iter  50 value 79.029021
iter  60 value 78.256211
iter  70 value 77.574080
iter  80 value 77.476281
iter  90 value 76.916527
iter 100 value 76.693184
final  value 76.693184 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 106.110134 
iter  10 value 91.884299
iter  20 value 84.013139
iter  30 value 82.328607
iter  40 value 81.371966
iter  50 value 81.044890
iter  60 value 78.605064
iter  70 value 77.834910
iter  80 value 77.564686
iter  90 value 77.372905
iter 100 value 77.290699
final  value 77.290699 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.995990 
final  value 94.486004 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.988183 
final  value 94.485779 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.442173 
iter  10 value 89.804682
iter  20 value 81.335410
iter  30 value 80.832074
iter  40 value 80.672335
iter  50 value 80.671004
iter  60 value 80.670001
final  value 80.669758 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.276021 
iter  10 value 94.486020
iter  20 value 94.484240
iter  30 value 93.209940
final  value 92.679976 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.330404 
iter  10 value 94.114699
iter  20 value 94.112191
iter  30 value 92.623384
iter  40 value 92.619747
final  value 92.619746 
converged
Fitting Repeat 1 

# weights:  305
initial  value 104.503849 
iter  10 value 94.489096
iter  20 value 94.484246
iter  30 value 94.199424
iter  40 value 92.680400
iter  40 value 92.680400
iter  40 value 92.680400
final  value 92.680400 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.360262 
iter  10 value 94.489404
iter  20 value 94.484247
iter  30 value 82.676848
iter  40 value 81.246830
iter  50 value 81.233798
iter  60 value 81.169644
iter  60 value 81.169643
iter  60 value 81.169643
final  value 81.169643 
converged
Fitting Repeat 3 

# weights:  305
initial  value 94.854837 
final  value 94.489745 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.477641 
iter  10 value 94.118715
iter  20 value 94.116417
iter  30 value 92.923278
iter  40 value 92.682930
iter  50 value 92.680739
iter  60 value 92.631169
final  value 92.620091 
converged
Fitting Repeat 5 

# weights:  305
initial  value 120.920136 
iter  10 value 94.489405
iter  20 value 93.334633
iter  30 value 85.653150
iter  40 value 85.649550
iter  40 value 85.649550
iter  40 value 85.649550
final  value 85.649550 
converged
Fitting Repeat 1 

# weights:  507
initial  value 108.010191 
iter  10 value 94.493214
iter  20 value 91.287451
iter  30 value 80.634325
iter  40 value 78.565092
iter  50 value 78.312481
iter  60 value 77.955646
iter  70 value 77.912540
final  value 77.912213 
converged
Fitting Repeat 2 

# weights:  507
initial  value 129.170419 
iter  10 value 94.121710
iter  20 value 94.114322
final  value 92.897166 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.503017 
iter  10 value 91.362595
iter  20 value 88.677802
iter  30 value 88.668805
iter  40 value 88.668253
iter  50 value 87.575046
iter  60 value 87.554655
iter  70 value 87.551960
iter  80 value 87.312344
iter  90 value 87.298223
iter 100 value 82.909399
final  value 82.909399 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 95.505658 
iter  10 value 94.120814
iter  20 value 94.113707
iter  30 value 92.654836
final  value 92.619539 
converged
Fitting Repeat 5 

# weights:  507
initial  value 103.626448 
iter  10 value 92.905357
iter  20 value 92.900158
iter  30 value 92.354870
iter  40 value 89.621670
iter  50 value 80.101987
iter  60 value 78.351648
iter  70 value 77.963009
iter  80 value 77.926019
iter  90 value 77.869619
iter 100 value 77.766259
final  value 77.766259 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.865669 
final  value 93.991525 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.695829 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.339534 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 101.090788 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.674907 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.866131 
iter  10 value 94.034684
final  value 94.032967 
converged
Fitting Repeat 2 

# weights:  305
initial  value 103.263179 
iter  10 value 92.475121
iter  20 value 92.462301
iter  30 value 92.462217
final  value 92.462212 
converged
Fitting Repeat 3 

# weights:  305
initial  value 104.999273 
final  value 94.008696 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.088898 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 98.486542 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.940828 
iter  10 value 94.022863
iter  20 value 90.174859
iter  30 value 87.036097
final  value 87.035863 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.056681 
iter  10 value 94.087455
final  value 94.050155 
converged
Fitting Repeat 3 

# weights:  507
initial  value 104.646782 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 101.834733 
final  value 94.032967 
converged
Fitting Repeat 5 

# weights:  507
initial  value 112.913716 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.446668 
iter  10 value 93.531351
iter  20 value 88.017500
iter  30 value 86.378609
iter  40 value 85.497096
iter  50 value 85.314284
iter  60 value 85.296690
iter  70 value 85.267822
final  value 85.263488 
converged
Fitting Repeat 2 

# weights:  103
initial  value 108.227923 
iter  10 value 94.049611
iter  20 value 90.444203
iter  30 value 90.036556
iter  40 value 88.054218
iter  50 value 86.024059
iter  60 value 85.956105
iter  70 value 85.457099
iter  80 value 85.325494
iter  90 value 85.264366
final  value 85.263488 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.989855 
iter  10 value 94.069592
iter  20 value 90.846436
iter  30 value 88.471235
iter  40 value 86.267065
iter  50 value 84.337337
iter  60 value 83.897257
iter  70 value 83.453548
iter  80 value 83.286346
iter  90 value 83.201536
iter 100 value 83.151606
final  value 83.151606 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 100.468028 
iter  10 value 93.987419
iter  20 value 89.123793
iter  30 value 87.681450
iter  40 value 87.113648
iter  50 value 85.937667
iter  60 value 85.676623
iter  70 value 85.599456
iter  80 value 85.554763
final  value 85.554195 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.622316 
iter  10 value 94.059837
iter  20 value 93.981925
iter  30 value 89.167503
iter  40 value 87.656523
iter  50 value 85.852620
iter  60 value 85.383888
iter  70 value 85.309151
iter  80 value 85.305312
iter  90 value 85.277876
iter 100 value 85.265973
final  value 85.265973 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 104.830124 
iter  10 value 94.421862
iter  20 value 94.067385
iter  30 value 86.637185
iter  40 value 86.225258
iter  50 value 85.780365
iter  60 value 83.741263
iter  70 value 83.020311
iter  80 value 82.669993
iter  90 value 82.245631
iter 100 value 82.183959
final  value 82.183959 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 100.785206 
iter  10 value 94.453544
iter  20 value 93.410165
iter  30 value 92.824391
iter  40 value 90.837667
iter  50 value 84.890419
iter  60 value 84.831425
iter  70 value 83.986737
iter  80 value 83.755012
iter  90 value 83.576506
iter 100 value 83.361912
final  value 83.361912 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 125.270006 
iter  10 value 93.857260
iter  20 value 89.692574
iter  30 value 88.334524
iter  40 value 87.486566
iter  50 value 84.669848
iter  60 value 83.575399
iter  70 value 83.258133
iter  80 value 82.702225
iter  90 value 82.312330
iter 100 value 82.300922
final  value 82.300922 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 114.223001 
iter  10 value 94.062408
iter  20 value 90.447107
iter  30 value 86.582132
iter  40 value 86.166382
iter  50 value 84.503875
iter  60 value 82.893730
iter  70 value 82.702360
iter  80 value 82.249287
iter  90 value 82.127009
iter 100 value 81.947928
final  value 81.947928 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 120.853658 
iter  10 value 94.488116
iter  20 value 90.332852
iter  30 value 87.194999
iter  40 value 84.753406
iter  50 value 83.515834
iter  60 value 83.224986
iter  70 value 83.017308
iter  80 value 82.794082
iter  90 value 82.503079
iter 100 value 82.314357
final  value 82.314357 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 108.560880 
iter  10 value 94.126951
iter  20 value 91.172842
iter  30 value 87.498428
iter  40 value 86.408625
iter  50 value 86.083590
iter  60 value 85.847054
iter  70 value 84.906992
iter  80 value 83.065608
iter  90 value 82.642944
iter 100 value 82.489141
final  value 82.489141 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.834247 
iter  10 value 94.553383
iter  20 value 93.415806
iter  30 value 86.849224
iter  40 value 86.160241
iter  50 value 84.595474
iter  60 value 82.663507
iter  70 value 82.486936
iter  80 value 82.203819
iter  90 value 82.012124
iter 100 value 81.877990
final  value 81.877990 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 107.203600 
iter  10 value 94.055188
iter  20 value 91.151714
iter  30 value 87.452651
iter  40 value 84.355467
iter  50 value 83.184737
iter  60 value 82.749522
iter  70 value 82.485463
iter  80 value 82.442504
iter  90 value 82.286222
iter 100 value 82.011515
final  value 82.011515 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 103.250376 
iter  10 value 91.398650
iter  20 value 86.214646
iter  30 value 85.456222
iter  40 value 85.060554
iter  50 value 83.792160
iter  60 value 82.821012
iter  70 value 82.758428
iter  80 value 82.613585
iter  90 value 82.074899
iter 100 value 81.903133
final  value 81.903133 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 105.352282 
iter  10 value 92.285792
iter  20 value 87.916799
iter  30 value 86.209606
iter  40 value 85.557736
iter  50 value 84.531541
iter  60 value 83.175746
iter  70 value 82.758056
iter  80 value 82.111388
iter  90 value 81.897780
iter 100 value 81.808988
final  value 81.808988 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 103.877689 
iter  10 value 94.054679
iter  20 value 93.944369
iter  30 value 87.310618
iter  40 value 85.945159
iter  50 value 85.643573
iter  60 value 85.633607
final  value 85.633593 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.961700 
final  value 94.054824 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.347523 
final  value 94.054743 
converged
Fitting Repeat 4 

# weights:  103
initial  value 115.424176 
final  value 94.054446 
converged
Fitting Repeat 5 

# weights:  103
initial  value 102.078266 
final  value 94.054387 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.062346 
iter  10 value 93.992098
iter  20 value 93.989286
iter  30 value 93.931651
iter  40 value 89.262197
iter  50 value 86.873685
iter  60 value 85.133888
iter  70 value 83.820288
iter  80 value 82.676425
iter  90 value 82.270240
iter 100 value 81.900451
final  value 81.900451 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.442081 
iter  10 value 94.057278
iter  20 value 93.889592
iter  30 value 89.051618
iter  40 value 87.536562
iter  50 value 87.523313
iter  60 value 86.827991
iter  70 value 86.778524
iter  80 value 86.765164
iter  90 value 86.756061
iter 100 value 86.619059
final  value 86.619059 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.956160 
iter  10 value 94.058475
iter  20 value 93.558111
iter  30 value 86.472077
iter  40 value 83.914547
iter  50 value 83.799334
iter  60 value 83.702039
final  value 83.702020 
converged
Fitting Repeat 4 

# weights:  305
initial  value 116.147843 
iter  10 value 94.037564
iter  20 value 94.033336
iter  30 value 93.975790
iter  40 value 91.915217
iter  50 value 85.449395
iter  60 value 84.216575
iter  70 value 82.647819
iter  80 value 82.492301
iter  90 value 82.443426
iter 100 value 82.441415
final  value 82.441415 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 96.672515 
iter  10 value 94.057704
iter  20 value 88.648889
iter  30 value 88.130582
iter  40 value 87.729873
iter  50 value 87.094611
iter  60 value 87.088855
iter  70 value 87.064209
iter  80 value 86.942674
iter  90 value 85.371566
iter 100 value 85.021988
final  value 85.021988 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 97.461521 
iter  10 value 92.846557
iter  20 value 92.674382
iter  30 value 92.260476
iter  40 value 90.975266
iter  50 value 88.605894
iter  60 value 85.717984
iter  70 value 85.571447
final  value 85.571440 
converged
Fitting Repeat 2 

# weights:  507
initial  value 113.127098 
iter  10 value 93.992713
iter  20 value 92.758172
iter  30 value 92.661766
iter  40 value 91.884023
iter  50 value 91.616170
iter  60 value 91.574077
iter  70 value 91.501049
iter  80 value 91.497779
iter  90 value 91.491024
final  value 91.490721 
converged
Fitting Repeat 3 

# weights:  507
initial  value 101.222368 
iter  10 value 93.918187
iter  20 value 93.891056
iter  30 value 93.378905
iter  40 value 87.386573
iter  50 value 87.382810
iter  60 value 87.366022
iter  70 value 85.364726
iter  80 value 85.189157
iter  90 value 84.999533
iter 100 value 84.964428
final  value 84.964428 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 97.427944 
iter  10 value 94.060055
iter  20 value 87.875841
iter  30 value 86.497455
iter  40 value 86.440973
iter  50 value 85.641468
iter  60 value 84.532041
iter  70 value 82.763160
iter  80 value 81.298479
iter  90 value 81.195510
iter 100 value 81.092598
final  value 81.092598 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 116.479518 
iter  10 value 86.755588
iter  20 value 85.373663
iter  30 value 85.369948
iter  40 value 85.362293
iter  50 value 85.296853
iter  60 value 85.296725
iter  70 value 85.295268
final  value 85.295222 
converged
Fitting Repeat 1 

# weights:  103
initial  value 98.564806 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 103.462631 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 105.059685 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.215765 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.655487 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 94.785718 
final  value 94.052911 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.029551 
final  value 93.567162 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.184895 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.121829 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 95.796653 
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 94.658295 
iter  10 value 93.545637
iter  20 value 93.544731
final  value 93.544713 
converged
Fitting Repeat 2 

# weights:  507
initial  value 102.137283 
iter  10 value 93.753868
final  value 93.582418 
converged
Fitting Repeat 3 

# weights:  507
initial  value 121.722410 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.241934 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.839540 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.719109 
iter  10 value 93.387321
iter  20 value 87.371740
iter  30 value 86.971722
iter  40 value 86.415459
iter  50 value 85.126918
iter  60 value 84.614591
iter  70 value 84.106020
iter  80 value 84.101548
iter  90 value 84.099126
final  value 84.094316 
converged
Fitting Repeat 2 

# weights:  103
initial  value 122.706507 
iter  10 value 94.065280
iter  20 value 93.787289
iter  30 value 87.147263
iter  40 value 86.577111
iter  50 value 86.450259
iter  60 value 86.048482
iter  70 value 85.395987
iter  80 value 84.960354
iter  90 value 84.657967
final  value 84.650443 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.766355 
iter  10 value 93.024972
iter  20 value 87.130004
iter  30 value 86.519363
iter  40 value 86.168430
iter  50 value 85.796828
iter  60 value 85.335239
iter  70 value 85.151691
final  value 85.151684 
converged
Fitting Repeat 4 

# weights:  103
initial  value 97.165679 
iter  10 value 94.055311
iter  20 value 94.054680
iter  30 value 92.254504
iter  40 value 89.595106
iter  50 value 89.473960
iter  60 value 87.857561
iter  70 value 86.850792
iter  80 value 86.424021
iter  90 value 86.210357
final  value 86.210354 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.886700 
iter  10 value 93.923072
iter  20 value 86.814020
iter  30 value 85.969618
iter  40 value 85.871834
iter  50 value 85.750383
iter  60 value 85.711195
final  value 85.711179 
converged
Fitting Repeat 1 

# weights:  305
initial  value 103.850759 
iter  10 value 93.993193
iter  20 value 93.220451
iter  30 value 88.738205
iter  40 value 87.048970
iter  50 value 86.424407
iter  60 value 85.451803
iter  70 value 85.204651
iter  80 value 84.992667
iter  90 value 84.058220
iter 100 value 83.120725
final  value 83.120725 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 106.735711 
iter  10 value 94.013784
iter  20 value 93.637831
iter  30 value 87.432234
iter  40 value 86.758418
iter  50 value 86.576659
iter  60 value 85.459708
iter  70 value 84.703120
iter  80 value 84.152039
iter  90 value 83.549780
iter 100 value 83.293685
final  value 83.293685 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.039176 
iter  10 value 94.129321
iter  20 value 94.005928
iter  30 value 93.645036
iter  40 value 89.560509
iter  50 value 88.043837
iter  60 value 87.571436
iter  70 value 86.416637
iter  80 value 85.293742
iter  90 value 84.611140
iter 100 value 83.195631
final  value 83.195631 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.415589 
iter  10 value 94.060341
iter  20 value 93.948548
iter  30 value 88.825990
iter  40 value 88.283955
iter  50 value 85.750875
iter  60 value 84.530819
iter  70 value 84.160538
iter  80 value 83.664742
iter  90 value 83.404369
iter 100 value 83.277486
final  value 83.277486 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 123.305193 
iter  10 value 94.051836
iter  20 value 91.505686
iter  30 value 88.283805
iter  40 value 87.182853
iter  50 value 85.711456
iter  60 value 83.611025
iter  70 value 83.298638
iter  80 value 83.048468
iter  90 value 82.795905
iter 100 value 82.652063
final  value 82.652063 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 118.537699 
iter  10 value 94.869053
iter  20 value 91.081160
iter  30 value 87.992469
iter  40 value 86.958015
iter  50 value 84.762120
iter  60 value 83.450207
iter  70 value 83.168126
iter  80 value 82.821854
iter  90 value 82.575508
iter 100 value 82.450820
final  value 82.450820 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 122.553033 
iter  10 value 94.110951
iter  20 value 89.703081
iter  30 value 87.332068
iter  40 value 86.463978
iter  50 value 85.323199
iter  60 value 83.634519
iter  70 value 83.258344
iter  80 value 82.948083
iter  90 value 82.553222
iter 100 value 82.433493
final  value 82.433493 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 115.989386 
iter  10 value 93.744060
iter  20 value 92.220411
iter  30 value 88.139429
iter  40 value 86.537134
iter  50 value 85.115553
iter  60 value 84.698955
iter  70 value 83.879340
iter  80 value 83.104486
iter  90 value 82.893343
iter 100 value 82.770658
final  value 82.770658 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 110.935441 
iter  10 value 93.479136
iter  20 value 89.883442
iter  30 value 87.669894
iter  40 value 86.766506
iter  50 value 85.618212
iter  60 value 84.951201
iter  70 value 84.839487
iter  80 value 84.412956
iter  90 value 84.042764
iter 100 value 83.784773
final  value 83.784773 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 123.475532 
iter  10 value 94.145165
iter  20 value 93.033696
iter  30 value 88.498876
iter  40 value 87.352303
iter  50 value 85.261930
iter  60 value 84.112882
iter  70 value 83.494034
iter  80 value 83.149109
iter  90 value 82.972193
iter 100 value 82.626355
final  value 82.626355 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.365022 
final  value 94.054715 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.351756 
final  value 94.054284 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.216385 
iter  10 value 94.054773
iter  20 value 94.052534
iter  30 value 93.585330
iter  40 value 93.582936
final  value 93.582919 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.996563 
final  value 93.584205 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.046292 
final  value 94.054625 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.449981 
iter  10 value 94.040075
iter  20 value 90.092035
iter  30 value 89.389655
iter  40 value 87.991599
iter  50 value 87.613347
iter  50 value 87.613347
final  value 87.613347 
converged
Fitting Repeat 2 

# weights:  305
initial  value 150.878133 
iter  10 value 94.057646
iter  20 value 94.053172
iter  30 value 92.462910
iter  40 value 87.341965
iter  50 value 87.335876
iter  60 value 87.180972
iter  70 value 85.024689
iter  80 value 84.923002
iter  90 value 84.921971
iter 100 value 84.921131
final  value 84.921131 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 116.299802 
iter  10 value 94.058279
iter  20 value 93.998001
iter  30 value 85.971561
iter  40 value 84.989968
iter  50 value 84.719536
iter  60 value 84.378781
iter  70 value 84.197953
iter  70 value 84.197953
iter  70 value 84.197953
final  value 84.197953 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.482644 
iter  10 value 94.057742
iter  20 value 93.857774
iter  30 value 87.758625
iter  40 value 87.157637
iter  40 value 87.157636
iter  40 value 87.157636
final  value 87.157636 
converged
Fitting Repeat 5 

# weights:  305
initial  value 94.265094 
iter  10 value 94.057448
iter  20 value 93.867605
iter  30 value 93.550265
iter  40 value 93.509482
iter  50 value 93.089082
iter  60 value 87.660835
iter  70 value 85.671530
iter  80 value 85.499452
final  value 85.497288 
converged
Fitting Repeat 1 

# weights:  507
initial  value 98.722956 
iter  10 value 93.679205
iter  20 value 93.672187
final  value 93.672116 
converged
Fitting Repeat 2 

# weights:  507
initial  value 96.058389 
iter  10 value 93.095289
iter  20 value 93.093183
iter  30 value 87.160103
iter  40 value 86.402728
final  value 86.402680 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.977267 
iter  10 value 93.590854
iter  20 value 93.582804
iter  30 value 93.532747
iter  40 value 93.528541
final  value 93.528538 
converged
Fitting Repeat 4 

# weights:  507
initial  value 103.899491 
final  value 94.060954 
converged
Fitting Repeat 5 

# weights:  507
initial  value 95.402709 
iter  10 value 93.849777
iter  20 value 93.694979
iter  30 value 93.617132
iter  40 value 93.613868
iter  50 value 93.099040
iter  60 value 93.084543
iter  70 value 93.045462
iter  80 value 93.029396
final  value 93.029364 
converged
Fitting Repeat 1 

# weights:  103
initial  value 102.767293 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.099637 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 97.637672 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 110.331405 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.694709 
iter  10 value 88.909265
iter  20 value 87.820112
final  value 87.820055 
converged
Fitting Repeat 1 

# weights:  305
initial  value 101.443205 
iter  10 value 86.777932
iter  20 value 85.072614
iter  30 value 84.990005
iter  40 value 84.974507
final  value 84.974481 
converged
Fitting Repeat 2 

# weights:  305
initial  value 102.008264 
iter  10 value 94.484137
iter  10 value 94.484137
iter  10 value 94.484137
final  value 94.484137 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.005288 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  305
initial  value 97.981163 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.896616 
final  value 94.466823 
converged
Fitting Repeat 1 

# weights:  507
initial  value 116.563745 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 100.233543 
iter  10 value 92.841776
iter  20 value 92.822940
final  value 92.822885 
converged
Fitting Repeat 3 

# weights:  507
initial  value 99.553583 
iter  10 value 93.423058
iter  20 value 93.413331
final  value 93.413318 
converged
Fitting Repeat 4 

# weights:  507
initial  value 114.298561 
final  value 94.466823 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.697657 
iter  10 value 92.440828
iter  20 value 92.363440
final  value 92.363316 
converged
Fitting Repeat 1 

# weights:  103
initial  value 100.216681 
iter  10 value 94.362045
iter  20 value 90.254237
iter  30 value 87.598944
iter  40 value 85.733409
iter  50 value 85.586124
iter  60 value 85.372415
iter  70 value 85.140436
final  value 85.128753 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.465632 
iter  10 value 94.874151
iter  20 value 93.926034
iter  30 value 87.202802
iter  40 value 87.026433
iter  50 value 86.815372
iter  60 value 86.424680
iter  70 value 85.625266
iter  80 value 85.350030
iter  90 value 84.677870
iter 100 value 84.180213
final  value 84.180213 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 105.357506 
iter  10 value 94.486435
iter  20 value 94.171311
iter  30 value 92.463909
iter  40 value 88.563515
iter  50 value 84.944731
iter  60 value 83.386413
iter  70 value 82.724122
iter  80 value 82.495010
iter  90 value 82.449308
iter 100 value 82.402955
final  value 82.402955 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 103.276622 
iter  10 value 94.494020
iter  20 value 90.601722
iter  30 value 90.260172
iter  40 value 87.214878
iter  50 value 86.697909
iter  60 value 84.693962
iter  70 value 84.314336
iter  80 value 84.282157
iter  90 value 84.273148
iter 100 value 84.168268
final  value 84.168268 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 97.005684 
iter  10 value 94.490579
iter  20 value 92.415773
iter  30 value 87.812346
iter  40 value 86.145582
iter  50 value 84.922796
iter  60 value 83.603367
iter  70 value 82.839334
iter  80 value 82.666805
iter  90 value 82.485111
iter 100 value 82.401732
final  value 82.401732 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 113.036489 
iter  10 value 94.517846
iter  20 value 88.559627
iter  30 value 83.705297
iter  40 value 82.568561
iter  50 value 82.227188
iter  60 value 82.008615
iter  70 value 81.527311
iter  80 value 81.354983
iter  90 value 81.271702
iter 100 value 81.130726
final  value 81.130726 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.626993 
iter  10 value 97.475005
iter  20 value 93.304598
iter  30 value 88.290203
iter  40 value 87.967649
iter  50 value 86.845546
iter  60 value 85.541215
iter  70 value 84.947510
iter  80 value 84.844629
iter  90 value 84.827659
iter 100 value 84.805029
final  value 84.805029 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.914904 
iter  10 value 94.407580
iter  20 value 93.989183
iter  30 value 89.456772
iter  40 value 86.078390
iter  50 value 84.038058
iter  60 value 83.438088
iter  70 value 82.914411
iter  80 value 81.995971
iter  90 value 81.666208
iter 100 value 81.409257
final  value 81.409257 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.634084 
iter  10 value 94.419855
iter  20 value 90.320014
iter  30 value 87.909020
iter  40 value 86.418235
iter  50 value 84.646422
iter  60 value 82.806492
iter  70 value 81.917733
iter  80 value 81.651235
iter  90 value 81.488045
iter 100 value 81.473197
final  value 81.473197 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 108.877126 
iter  10 value 94.326898
iter  20 value 88.409325
iter  30 value 87.599465
iter  40 value 87.515920
iter  50 value 85.300090
iter  60 value 84.880569
iter  70 value 84.772395
iter  80 value 84.736342
iter  90 value 84.696652
iter 100 value 84.044743
final  value 84.044743 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 105.777062 
iter  10 value 94.493076
iter  20 value 89.050693
iter  30 value 87.501278
iter  40 value 84.424534
iter  50 value 83.071849
iter  60 value 82.625225
iter  70 value 82.485776
iter  80 value 82.220186
iter  90 value 82.076574
iter 100 value 81.337959
final  value 81.337959 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 108.755343 
iter  10 value 94.923773
iter  20 value 86.430208
iter  30 value 85.850253
iter  40 value 85.126129
iter  50 value 83.674638
iter  60 value 83.206039
iter  70 value 82.188750
iter  80 value 81.392152
iter  90 value 81.214840
iter 100 value 80.878974
final  value 80.878974 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 109.300226 
iter  10 value 94.532663
iter  20 value 89.766329
iter  30 value 88.020387
iter  40 value 86.877729
iter  50 value 85.872382
iter  60 value 85.569521
iter  70 value 83.102304
iter  80 value 82.439143
iter  90 value 81.706556
iter 100 value 81.411196
final  value 81.411196 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.428255 
iter  10 value 95.166685
iter  20 value 94.835486
iter  30 value 91.673306
iter  40 value 87.703074
iter  50 value 87.222112
iter  60 value 87.008384
iter  70 value 86.838377
iter  80 value 85.700789
iter  90 value 82.871337
iter 100 value 81.669530
final  value 81.669530 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 108.017462 
iter  10 value 95.048331
iter  20 value 94.045238
iter  30 value 88.596635
iter  40 value 84.829622
iter  50 value 83.964162
iter  60 value 82.240746
iter  70 value 81.733197
iter  80 value 81.533082
iter  90 value 81.427984
iter 100 value 81.356631
final  value 81.356631 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 101.738397 
final  value 94.485890 
converged
Fitting Repeat 2 

# weights:  103
initial  value 97.835867 
final  value 94.485898 
converged
Fitting Repeat 3 

# weights:  103
initial  value 106.262647 
final  value 94.485714 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.057511 
final  value 94.485811 
converged
Fitting Repeat 5 

# weights:  103
initial  value 97.160889 
final  value 94.486173 
converged
Fitting Repeat 1 

# weights:  305
initial  value 95.936112 
iter  10 value 94.488701
iter  20 value 94.404007
iter  30 value 93.723654
iter  40 value 89.823115
iter  50 value 84.914874
iter  60 value 84.780536
iter  70 value 84.778900
iter  80 value 84.403863
iter  90 value 83.967834
iter 100 value 83.174648
final  value 83.174648 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.728454 
iter  10 value 94.488042
iter  20 value 94.375215
iter  30 value 88.149041
iter  40 value 86.948695
iter  50 value 85.648775
iter  60 value 85.642961
iter  60 value 85.642961
iter  60 value 85.642961
final  value 85.642961 
converged
Fitting Repeat 3 

# weights:  305
initial  value 100.408828 
iter  10 value 94.488657
iter  20 value 94.396570
iter  30 value 85.565828
iter  40 value 85.483413
iter  50 value 85.245537
iter  60 value 85.205932
iter  70 value 85.204047
iter  80 value 85.177680
iter  90 value 85.131429
iter 100 value 85.131362
final  value 85.131362 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.397118 
iter  10 value 94.471965
iter  20 value 94.467105
final  value 94.466893 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.952605 
iter  10 value 94.318932
iter  20 value 94.315294
iter  30 value 94.312077
iter  40 value 94.161716
iter  50 value 94.141984
iter  60 value 91.645574
iter  70 value 90.414582
iter  80 value 90.377563
iter  90 value 90.073404
iter 100 value 90.010927
final  value 90.010927 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 119.424567 
iter  10 value 94.474621
iter  20 value 93.511974
iter  30 value 93.482166
iter  40 value 93.477290
iter  50 value 88.308871
iter  60 value 87.242121
iter  70 value 87.227217
final  value 87.225865 
converged
Fitting Repeat 2 

# weights:  507
initial  value 95.816217 
iter  10 value 94.492382
iter  20 value 94.483108
iter  30 value 88.579799
iter  40 value 88.167823
iter  50 value 84.115851
iter  60 value 82.428638
iter  70 value 82.001933
iter  80 value 81.827280
iter  90 value 81.826477
iter 100 value 81.826035
final  value 81.826035 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 96.050840 
iter  10 value 94.487804
iter  20 value 94.471222
iter  30 value 94.389476
final  value 94.387792 
converged
Fitting Repeat 4 

# weights:  507
initial  value 99.369549 
iter  10 value 94.474596
iter  20 value 94.048387
iter  30 value 85.795510
iter  40 value 82.427369
iter  50 value 82.137448
iter  60 value 82.046861
iter  70 value 81.709000
iter  80 value 81.264968
iter  90 value 80.565960
iter 100 value 79.651534
final  value 79.651534 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 97.931901 
iter  10 value 94.174680
iter  20 value 94.081446
iter  30 value 93.940054
iter  40 value 93.920988
iter  50 value 93.902618
iter  60 value 93.900379
final  value 93.900069 
converged
Fitting Repeat 1 

# weights:  507
initial  value 150.107994 
iter  10 value 116.702534
iter  20 value 107.960418
iter  30 value 104.724478
iter  40 value 102.198998
iter  50 value 101.513711
iter  60 value 101.213071
iter  70 value 101.017909
iter  80 value 100.785069
iter  90 value 100.390803
iter 100 value 100.371524
final  value 100.371524 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 135.233586 
iter  10 value 117.887207
iter  20 value 115.683963
iter  30 value 107.890042
iter  40 value 106.459582
iter  50 value 105.532499
iter  60 value 104.947927
iter  70 value 104.356816
iter  80 value 104.246763
iter  90 value 103.975445
iter 100 value 102.374050
final  value 102.374050 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 142.745257 
iter  10 value 116.085853
iter  20 value 107.616229
iter  30 value 105.938041
iter  40 value 102.896691
iter  50 value 102.087444
iter  60 value 101.622131
iter  70 value 101.436181
iter  80 value 101.344248
iter  90 value 101.154073
iter 100 value 101.006497
final  value 101.006497 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 140.943897 
iter  10 value 120.652163
iter  20 value 117.649088
iter  30 value 110.242248
iter  40 value 109.661948
iter  50 value 106.268315
iter  60 value 105.668446
iter  70 value 105.207847
iter  80 value 104.831553
iter  90 value 102.232468
iter 100 value 101.260203
final  value 101.260203 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 142.413988 
iter  10 value 119.336130
iter  20 value 117.616955
iter  30 value 108.712241
iter  40 value 105.594030
iter  50 value 104.669925
iter  60 value 103.726012
iter  70 value 102.728739
iter  80 value 102.219343
iter  90 value 101.789349
iter 100 value 101.450949
final  value 101.450949 
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 00:13:27 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 
 42.400   2.116  46.697 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod34.787 0.65335.439
FreqInteractors0.2300.0150.246
calculateAAC0.0320.0120.044
calculateAutocor0.2880.0230.313
calculateCTDC0.0730.0010.073
calculateCTDD0.5420.0000.542
calculateCTDT0.2270.0000.226
calculateCTriad0.3570.0150.373
calculateDC0.0860.0050.090
calculateF0.2990.0040.303
calculateKSAAP0.0890.0070.096
calculateQD_Sm1.6560.0691.724
calculateTC1.4980.1481.646
calculateTC_Sm0.2820.0040.286
corr_plot34.502 0.29634.799
enrichfindP 0.458 0.04212.046
enrichfind_hp0.0810.0051.356
enrichplot0.3480.0280.376
filter_missing_values0.0000.0020.001
getFASTA0.4180.0054.708
getHPI0.0010.0010.001
get_negativePPI0.0000.0020.003
get_positivePPI0.0000.0000.001
impute_missing_data0.0020.0010.003
plotPPI0.0700.0100.082
pred_ensembel13.473 0.65710.880
var_imp36.442 0.93137.374