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 11:37:55 -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 palomino3


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: F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz
StartedAt: 2024-05-04 04:25:57 -0400 (Sat, 04 May 2024)
EndedAt: 2024-05-04 04:30:44 -0400 (Sat, 04 May 2024)
EllapsedTime: 287.0 seconds
RetCode: 0
Status:   OK  
CheckDir: HPiP.Rcheck
Warnings: 0

Command output

##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.19-bioc\R\library --no-vignettes --timings HPiP_1.10.0.tar.gz
###
##############################################################################
##############################################################################


* using log directory 'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck'
* using R version 4.4.0 beta (2024-04-15 r86425 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
    gcc.exe (GCC) 13.2.0
    GNU Fortran (GCC) 13.2.0
* running under: Windows Server 2022 x64 (build 20348)
* 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 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 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
FSmethod      32.00   2.14   34.22
var_imp       31.13   1.30   32.44
corr_plot     29.71   2.03   31.73
pred_ensembel 14.25   0.64   10.69
enrichfindP    0.58   0.22   17.82
* 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
  'F:/biocbuild/bbs-3.19-bioc/meat/HPiP.Rcheck/00check.log'
for details.


Installation output

HPiP.Rcheck/00install.out

##############################################################################
##############################################################################
###
### Running command:
###
###   F:\biocbuild\bbs-3.19-bioc\R\bin\R.exe CMD INSTALL HPiP
###
##############################################################################
##############################################################################


* installing to library 'F:/biocbuild/bbs-3.19-bioc/R/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 ucrt) -- "Puppy Cup"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64

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 98.366514 
iter  10 value 93.818713
iter  10 value 93.818713
iter  10 value 93.818713
final  value 93.818713 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.376345 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.196576 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 96.203416 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.441032 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.582149 
final  value 93.981595 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.558016 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 107.973849 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  305
initial  value 100.884093 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.976180 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  507
initial  value 101.180758 
iter  10 value 92.620299
iter  20 value 86.067321
iter  30 value 86.063420
final  value 86.063406 
converged
Fitting Repeat 2 

# weights:  507
initial  value 98.096441 
iter  10 value 93.875448
final  value 93.875386 
converged
Fitting Repeat 3 

# weights:  507
initial  value 94.970950 
final  value 94.032967 
converged
Fitting Repeat 4 

# weights:  507
initial  value 118.092257 
final  value 94.052910 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.512387 
iter  10 value 93.327756
final  value 93.326351 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.830042 
iter  10 value 94.048037
iter  20 value 87.151073
iter  30 value 86.234764
iter  40 value 86.087252
iter  50 value 85.432824
iter  60 value 82.583957
iter  70 value 82.250856
iter  80 value 82.225427
iter  90 value 82.216231
iter 100 value 82.215821
final  value 82.215821 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 104.152036 
iter  10 value 94.517721
iter  20 value 87.154170
iter  30 value 86.034636
iter  40 value 82.334457
iter  50 value 82.229245
iter  60 value 82.203298
final  value 82.202797 
converged
Fitting Repeat 3 

# weights:  103
initial  value 103.597795 
iter  10 value 90.869845
iter  20 value 84.531855
iter  30 value 84.123367
iter  40 value 84.095307
iter  50 value 82.650802
iter  60 value 82.543299
iter  70 value 82.375059
iter  80 value 82.206547
iter  90 value 82.202802
final  value 82.202797 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.350962 
iter  10 value 94.078662
iter  20 value 93.153943
iter  30 value 92.967677
iter  40 value 92.967125
iter  50 value 92.963325
iter  60 value 89.192272
iter  70 value 87.704197
iter  80 value 87.437069
iter  90 value 82.018448
iter 100 value 81.783389
final  value 81.783389 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 106.492956 
final  value 94.056700 
converged
Fitting Repeat 1 

# weights:  305
initial  value 110.693768 
iter  10 value 94.272071
iter  20 value 88.585085
iter  30 value 83.241556
iter  40 value 82.192204
iter  50 value 81.966079
iter  60 value 81.879717
iter  70 value 81.547346
iter  80 value 79.151240
iter  90 value 78.720759
iter 100 value 78.323093
final  value 78.323093 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 102.248385 
iter  10 value 89.677932
iter  20 value 82.102382
iter  30 value 81.866059
iter  40 value 81.325994
iter  50 value 81.206612
iter  60 value 81.173895
iter  70 value 81.162256
iter  80 value 80.705372
iter  90 value 79.326409
iter 100 value 78.737710
final  value 78.737710 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 105.669665 
iter  10 value 93.850278
iter  20 value 91.009006
iter  30 value 83.778543
iter  40 value 82.071332
iter  50 value 81.811851
iter  60 value 81.364032
iter  70 value 80.749995
iter  80 value 79.260622
iter  90 value 79.016988
iter 100 value 78.895914
final  value 78.895914 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 108.953818 
iter  10 value 94.050323
iter  20 value 93.010693
iter  30 value 89.799810
iter  40 value 85.450154
iter  50 value 82.988553
iter  60 value 81.578146
iter  70 value 80.976120
iter  80 value 79.758779
iter  90 value 79.316261
iter 100 value 78.845967
final  value 78.845967 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 134.745878 
iter  10 value 94.437211
iter  20 value 93.583806
iter  30 value 93.345073
iter  40 value 84.737470
iter  50 value 82.766840
iter  60 value 79.909919
iter  70 value 79.135013
iter  80 value 78.931066
iter  90 value 78.597436
iter 100 value 77.820239
final  value 77.820239 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.230666 
iter  10 value 94.010637
iter  20 value 84.956782
iter  30 value 82.471756
iter  40 value 82.049092
iter  50 value 81.887589
iter  60 value 81.481095
iter  70 value 79.183016
iter  80 value 78.011707
iter  90 value 77.945860
iter 100 value 77.815606
final  value 77.815606 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 124.553384 
iter  10 value 98.770527
iter  20 value 92.875742
iter  30 value 84.819217
iter  40 value 81.827006
iter  50 value 80.837752
iter  60 value 79.132630
iter  70 value 78.945422
iter  80 value 78.693331
iter  90 value 78.652644
iter 100 value 78.326026
final  value 78.326026 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 119.715117 
iter  10 value 88.437917
iter  20 value 82.759443
iter  30 value 81.998484
iter  40 value 81.482492
iter  50 value 79.478579
iter  60 value 79.128274
iter  70 value 79.023904
iter  80 value 78.641993
iter  90 value 78.519964
iter 100 value 78.409116
final  value 78.409116 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 122.327891 
iter  10 value 94.107283
iter  20 value 93.442078
iter  30 value 93.292416
iter  40 value 83.712255
iter  50 value 79.310225
iter  60 value 79.025858
iter  70 value 78.629890
iter  80 value 78.207180
iter  90 value 77.522095
iter 100 value 77.097891
final  value 77.097891 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 122.693448 
iter  10 value 94.864001
iter  20 value 85.311202
iter  30 value 83.729322
iter  40 value 80.402978
iter  50 value 79.443984
iter  60 value 78.748607
iter  70 value 77.723123
iter  80 value 77.306562
iter  90 value 77.224377
iter 100 value 77.207837
final  value 77.207837 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 96.640121 
iter  10 value 93.822099
iter  20 value 93.811704
iter  30 value 93.811439
iter  40 value 93.810353
final  value 93.810312 
converged
Fitting Repeat 2 

# weights:  103
initial  value 95.478353 
final  value 94.054442 
converged
Fitting Repeat 3 

# weights:  103
initial  value 95.741223 
final  value 94.054562 
converged
Fitting Repeat 4 

# weights:  103
initial  value 99.382321 
final  value 94.054383 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.169216 
final  value 94.054741 
converged
Fitting Repeat 1 

# weights:  305
initial  value 96.362929 
iter  10 value 92.775667
iter  20 value 92.689641
iter  30 value 92.506277
iter  40 value 92.505007
iter  50 value 92.503773
iter  60 value 92.502422
final  value 92.502413 
converged
Fitting Repeat 2 

# weights:  305
initial  value 105.695398 
iter  10 value 94.059588
iter  20 value 93.957980
iter  30 value 93.332429
iter  40 value 93.195141
iter  50 value 93.189855
iter  60 value 84.843901
final  value 84.840730 
converged
Fitting Repeat 3 

# weights:  305
initial  value 105.168974 
iter  10 value 94.037952
iter  20 value 94.033089
iter  30 value 93.544222
iter  40 value 92.381310
iter  50 value 85.370229
iter  60 value 78.271963
iter  70 value 78.168882
iter  80 value 78.142191
final  value 78.142156 
converged
Fitting Repeat 4 

# weights:  305
initial  value 112.067821 
iter  10 value 93.609170
iter  20 value 93.350735
iter  30 value 86.858086
iter  40 value 81.920588
iter  50 value 78.864228
iter  60 value 77.419517
iter  70 value 77.380052
final  value 77.379902 
converged
Fitting Repeat 5 

# weights:  305
initial  value 113.851989 
iter  10 value 94.039810
iter  20 value 93.989493
iter  30 value 81.172930
iter  40 value 81.148426
iter  50 value 81.142005
final  value 81.141956 
converged
Fitting Repeat 1 

# weights:  507
initial  value 103.979376 
iter  10 value 94.064047
iter  20 value 93.444495
iter  30 value 88.036168
iter  40 value 86.721549
iter  50 value 84.751727
iter  60 value 83.514238
iter  70 value 78.167363
iter  80 value 78.077271
final  value 78.072126 
converged
Fitting Repeat 2 

# weights:  507
initial  value 97.970221 
iter  10 value 92.276174
iter  20 value 91.262288
iter  30 value 91.256807
iter  40 value 90.579521
iter  50 value 82.830023
iter  60 value 80.988018
iter  70 value 80.749205
final  value 80.748933 
converged
Fitting Repeat 3 

# weights:  507
initial  value 95.044637 
iter  10 value 94.055664
iter  20 value 84.181582
iter  30 value 83.246715
iter  40 value 83.242867
iter  50 value 81.194682
iter  60 value 80.209908
iter  70 value 78.982704
iter  80 value 77.791982
iter  90 value 77.782122
final  value 77.781678 
converged
Fitting Repeat 4 

# weights:  507
initial  value 110.913902 
iter  10 value 94.061558
iter  20 value 94.045731
iter  30 value 83.675101
iter  40 value 81.086404
iter  50 value 78.215138
iter  60 value 76.914323
iter  70 value 76.510499
iter  80 value 76.506708
iter  90 value 76.505835
iter 100 value 76.504303
final  value 76.504303 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 98.014785 
iter  10 value 93.827208
iter  20 value 91.501631
iter  30 value 81.186116
iter  40 value 81.013872
iter  50 value 80.973313
iter  60 value 80.969763
final  value 80.969412 
converged
Fitting Repeat 1 

# weights:  103
initial  value 95.386069 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 111.113370 
final  value 94.354396 
converged
Fitting Repeat 3 

# weights:  103
initial  value 108.592763 
final  value 94.354396 
converged
Fitting Repeat 4 

# weights:  103
initial  value 94.491805 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.042009 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 108.214273 
final  value 94.354396 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.641361 
iter  10 value 93.621336
final  value 93.621189 
converged
Fitting Repeat 3 

# weights:  305
initial  value 98.921943 
iter  10 value 92.210983
final  value 92.186364 
converged
Fitting Repeat 4 

# weights:  305
initial  value 101.815943 
iter  10 value 94.307939
final  value 94.046703 
converged
Fitting Repeat 5 

# weights:  305
initial  value 100.362996 
final  value 94.289216 
converged
Fitting Repeat 1 

# weights:  507
initial  value 118.480949 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.210784 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  507
initial  value 106.648114 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 106.969356 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.055721 
final  value 94.354396 
converged
Fitting Repeat 1 

# weights:  103
initial  value 111.344329 
iter  10 value 94.473259
iter  20 value 92.374413
iter  30 value 91.613332
iter  40 value 91.578654
iter  50 value 88.145556
iter  60 value 84.620447
iter  70 value 84.320856
iter  80 value 84.165312
iter  90 value 82.861721
iter 100 value 82.361085
final  value 82.361085 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 108.077999 
iter  10 value 94.374970
iter  20 value 88.885102
iter  30 value 88.292891
iter  40 value 87.550407
iter  50 value 87.297401
iter  60 value 86.056427
iter  70 value 85.905876
iter  70 value 85.905876
final  value 85.905876 
converged
Fitting Repeat 3 

# weights:  103
initial  value 100.127934 
iter  10 value 94.485589
iter  20 value 88.632970
iter  30 value 87.368710
iter  40 value 85.309185
iter  50 value 83.229412
iter  60 value 82.887583
iter  70 value 82.447479
iter  80 value 82.373278
iter  90 value 82.304934
iter 100 value 82.291542
final  value 82.291542 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.225878 
iter  10 value 94.489717
iter  20 value 94.486612
iter  30 value 94.295777
iter  40 value 93.832478
iter  50 value 93.654370
iter  60 value 91.611627
iter  70 value 84.813253
iter  80 value 83.778416
iter  90 value 83.552190
iter 100 value 83.494310
final  value 83.494310 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  103
initial  value 98.789788 
iter  10 value 94.487935
iter  20 value 94.395263
iter  30 value 94.382825
iter  40 value 94.373485
iter  50 value 93.868776
iter  60 value 89.485288
iter  70 value 85.757711
iter  80 value 83.965887
iter  90 value 83.258271
iter 100 value 83.054893
final  value 83.054893 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 106.608581 
iter  10 value 94.352245
iter  20 value 89.099021
iter  30 value 86.829524
iter  40 value 85.332457
iter  50 value 82.736003
iter  60 value 81.865432
iter  70 value 81.452370
iter  80 value 81.374832
iter  90 value 81.339167
iter 100 value 81.277031
final  value 81.277031 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.706230 
iter  10 value 94.508880
iter  20 value 93.006301
iter  30 value 89.036989
iter  40 value 88.421870
iter  50 value 85.192980
iter  60 value 84.072073
iter  70 value 83.761165
iter  80 value 83.478742
iter  90 value 83.035975
iter 100 value 82.296568
final  value 82.296568 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 113.342820 
iter  10 value 94.978139
iter  20 value 93.997360
iter  30 value 93.911133
iter  40 value 93.814516
iter  50 value 90.666463
iter  60 value 87.178542
iter  70 value 85.605116
iter  80 value 82.923688
iter  90 value 81.813583
iter 100 value 81.723667
final  value 81.723667 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 103.123922 
iter  10 value 94.188341
iter  20 value 88.260928
iter  30 value 87.679126
iter  40 value 87.434954
iter  50 value 87.071320
iter  60 value 85.934465
iter  70 value 85.643202
iter  80 value 85.236155
iter  90 value 83.493994
iter 100 value 82.931289
final  value 82.931289 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 107.034565 
iter  10 value 94.450983
iter  20 value 87.070312
iter  30 value 86.194552
iter  40 value 85.930255
iter  50 value 85.853143
iter  60 value 84.756648
iter  70 value 83.941861
iter  80 value 83.664261
iter  90 value 83.512195
iter 100 value 83.482277
final  value 83.482277 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 110.211527 
iter  10 value 94.401648
iter  20 value 89.771682
iter  30 value 84.842448
iter  40 value 84.186548
iter  50 value 83.459174
iter  60 value 82.504522
iter  70 value 81.436229
iter  80 value 80.955818
iter  90 value 80.828751
iter 100 value 80.686718
final  value 80.686718 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 105.873505 
iter  10 value 94.478640
iter  20 value 89.497601
iter  30 value 86.506310
iter  40 value 85.777074
iter  50 value 84.944726
iter  60 value 84.022710
iter  70 value 82.615600
iter  80 value 81.380522
iter  90 value 81.050716
iter 100 value 80.909714
final  value 80.909714 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 108.130110 
iter  10 value 94.252314
iter  20 value 87.780167
iter  30 value 87.212189
iter  40 value 87.113872
iter  50 value 84.413818
iter  60 value 83.171987
iter  70 value 82.660913
iter  80 value 81.973513
iter  90 value 81.484703
iter 100 value 81.221795
final  value 81.221795 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 123.178815 
iter  10 value 94.408925
iter  20 value 86.919190
iter  30 value 84.057652
iter  40 value 82.704310
iter  50 value 82.255716
iter  60 value 81.755997
iter  70 value 81.692803
iter  80 value 81.481303
iter  90 value 81.345024
iter 100 value 81.291927
final  value 81.291927 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 104.199328 
iter  10 value 95.350987
iter  20 value 92.573120
iter  30 value 88.261355
iter  40 value 84.655676
iter  50 value 83.366256
iter  60 value 82.136233
iter  70 value 81.909459
iter  80 value 81.876162
iter  90 value 81.842645
iter 100 value 81.688276
final  value 81.688276 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 105.045907 
final  value 94.485931 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.291523 
final  value 94.485998 
converged
Fitting Repeat 3 

# weights:  103
initial  value 99.776308 
final  value 94.485552 
converged
Fitting Repeat 4 

# weights:  103
initial  value 106.337185 
iter  10 value 91.184934
iter  20 value 91.155044
iter  30 value 91.154228
iter  40 value 91.153129
iter  50 value 91.152999
iter  60 value 91.120799
iter  70 value 91.110249
final  value 91.110168 
converged
Fitting Repeat 5 

# weights:  103
initial  value 95.719912 
final  value 94.485838 
converged
Fitting Repeat 1 

# weights:  305
initial  value 98.473814 
iter  10 value 94.488790
iter  20 value 93.725452
iter  30 value 91.791359
iter  40 value 91.407691
iter  50 value 91.103460
iter  60 value 91.074094
iter  70 value 91.073587
final  value 91.073582 
converged
Fitting Repeat 2 

# weights:  305
initial  value 107.553326 
iter  10 value 94.388463
iter  20 value 92.492856
iter  30 value 92.216693
iter  40 value 87.038404
iter  50 value 86.812976
iter  60 value 86.796356
iter  70 value 86.791542
iter  70 value 86.791541
final  value 86.791541 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.420933 
iter  10 value 94.488599
iter  20 value 94.475254
iter  30 value 93.812791
iter  40 value 91.456615
iter  50 value 86.403604
iter  60 value 86.106899
iter  70 value 86.105282
iter  80 value 86.102816
final  value 86.102246 
converged
Fitting Repeat 4 

# weights:  305
initial  value 114.454169 
iter  10 value 94.489252
iter  20 value 94.484309
iter  30 value 92.113185
iter  40 value 89.842741
iter  50 value 86.434402
iter  60 value 86.407333
iter  70 value 86.270517
iter  80 value 86.268523
iter  90 value 86.267551
iter 100 value 86.230386
final  value 86.230386 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 95.056184 
iter  10 value 94.359463
iter  20 value 93.865065
iter  30 value 93.724364
iter  40 value 93.724207
final  value 93.723786 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.839490 
iter  10 value 94.491277
iter  20 value 94.446539
iter  30 value 91.846439
iter  40 value 91.821608
iter  50 value 91.816107
iter  60 value 91.549554
iter  70 value 87.534269
iter  80 value 87.409157
iter  90 value 87.024629
iter 100 value 86.658780
final  value 86.658780 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 112.187021 
iter  10 value 93.879847
iter  20 value 93.872047
iter  30 value 93.660926
final  value 93.535991 
converged
Fitting Repeat 3 

# weights:  507
initial  value 115.029087 
iter  10 value 94.489417
iter  20 value 94.442115
iter  30 value 92.912223
iter  40 value 91.172951
iter  50 value 91.158658
iter  60 value 91.158280
iter  70 value 91.156642
iter  80 value 91.154849
iter  90 value 91.154602
iter 100 value 84.668925
final  value 84.668925 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 96.696162 
iter  10 value 93.732499
iter  20 value 93.731234
iter  30 value 93.162495
iter  40 value 93.152119
iter  50 value 93.150646
iter  60 value 93.119935
iter  70 value 93.118396
final  value 93.118394 
converged
Fitting Repeat 5 

# weights:  507
initial  value 101.095849 
iter  10 value 93.691013
iter  20 value 93.689654
iter  30 value 93.678023
iter  40 value 93.557862
iter  50 value 90.285208
iter  60 value 86.932785
iter  70 value 86.804039
iter  80 value 84.677319
iter  90 value 84.418762
iter 100 value 84.395041
final  value 84.395041 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 108.516102 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  103
initial  value 94.929076 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  103
initial  value 113.378612 
final  value 94.052910 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.216320 
iter  10 value 91.788183
iter  20 value 87.913614
iter  30 value 85.472639
final  value 85.462600 
converged
Fitting Repeat 5 

# weights:  103
initial  value 100.321100 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.858958 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  305
initial  value 97.438305 
final  value 94.052910 
converged
Fitting Repeat 3 

# weights:  305
initial  value 97.809719 
final  value 93.559524 
converged
Fitting Repeat 4 

# weights:  305
initial  value 94.505800 
iter  10 value 93.900469
final  value 93.900002 
converged
Fitting Repeat 5 

# weights:  305
initial  value 109.140350 
iter  10 value 93.877458
final  value 93.582418 
converged
Fitting Repeat 1 

# weights:  507
initial  value 96.815794 
final  value 94.052910 
converged
Fitting Repeat 2 

# weights:  507
initial  value 107.234847 
final  value 93.371808 
converged
Fitting Repeat 3 

# weights:  507
initial  value 107.752817 
final  value 93.582418 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.588688 
iter  10 value 94.053159
final  value 94.052911 
converged
Fitting Repeat 5 

# weights:  507
initial  value 105.596013 
final  value 94.052910 
converged
Fitting Repeat 1 

# weights:  103
initial  value 122.475765 
iter  10 value 94.085458
iter  20 value 93.987571
iter  30 value 88.228834
iter  40 value 86.090297
iter  50 value 85.531335
iter  60 value 85.444121
iter  70 value 85.098579
iter  80 value 84.168978
iter  90 value 83.725138
iter 100 value 83.709055
final  value 83.709055 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  103
initial  value 111.989242 
iter  10 value 93.936793
iter  20 value 93.704371
iter  30 value 89.161044
iter  40 value 86.129724
iter  50 value 83.654560
iter  60 value 82.870816
iter  70 value 82.291039
iter  80 value 82.199161
iter  90 value 82.185272
iter 100 value 82.175650
final  value 82.175650 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 97.409195 
iter  10 value 94.066230
iter  20 value 93.617122
iter  30 value 92.805193
iter  40 value 91.558215
iter  50 value 87.009808
iter  60 value 86.093057
iter  70 value 85.666208
iter  80 value 83.970348
iter  90 value 83.533448
iter 100 value 83.458387
final  value 83.458387 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 102.226574 
iter  10 value 94.057576
iter  20 value 90.719937
iter  30 value 87.059421
iter  40 value 86.271927
iter  50 value 85.404380
iter  60 value 83.580823
iter  70 value 83.458432
final  value 83.458384 
converged
Fitting Repeat 5 

# weights:  103
initial  value 101.211348 
iter  10 value 94.012897
iter  20 value 89.678985
iter  30 value 88.792065
iter  40 value 88.014314
iter  50 value 85.378558
iter  60 value 84.019953
iter  70 value 83.911352
iter  80 value 83.849873
final  value 83.849755 
converged
Fitting Repeat 1 

# weights:  305
initial  value 100.476278 
iter  10 value 89.925890
iter  20 value 85.187510
iter  30 value 84.590245
iter  40 value 84.392084
iter  50 value 83.782236
iter  60 value 83.192838
iter  70 value 83.165911
iter  80 value 83.149381
iter  90 value 82.930538
iter 100 value 82.198929
final  value 82.198929 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 123.880417 
iter  10 value 94.066616
iter  20 value 89.833194
iter  30 value 86.824998
iter  40 value 86.010715
iter  50 value 84.695482
iter  60 value 83.879966
iter  70 value 83.709049
iter  80 value 83.592083
iter  90 value 83.194188
iter 100 value 82.552812
final  value 82.552812 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 101.353712 
iter  10 value 93.548023
iter  20 value 88.788698
iter  30 value 83.518551
iter  40 value 82.371988
iter  50 value 81.564185
iter  60 value 81.023640
iter  70 value 80.753360
iter  80 value 80.575048
iter  90 value 80.330640
iter 100 value 80.216749
final  value 80.216749 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 104.504342 
iter  10 value 94.066764
iter  20 value 94.055096
iter  30 value 93.665793
iter  40 value 93.569169
iter  50 value 89.364768
iter  60 value 83.801373
iter  70 value 81.639040
iter  80 value 80.824192
iter  90 value 80.449097
iter 100 value 80.379403
final  value 80.379403 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 104.606839 
iter  10 value 94.029598
iter  20 value 91.418135
iter  30 value 87.971741
iter  40 value 86.082404
iter  50 value 83.562752
iter  60 value 82.288096
iter  70 value 81.393943
iter  80 value 81.017130
iter  90 value 80.743078
iter 100 value 80.646650
final  value 80.646650 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 109.054291 
iter  10 value 94.142812
iter  20 value 92.260909
iter  30 value 88.038779
iter  40 value 87.706775
iter  50 value 83.175542
iter  60 value 82.113011
iter  70 value 81.255297
iter  80 value 80.516290
iter  90 value 80.166130
iter 100 value 80.066863
final  value 80.066863 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.456004 
iter  10 value 94.150967
iter  20 value 93.364261
iter  30 value 90.880988
iter  40 value 87.027165
iter  50 value 85.487786
iter  60 value 82.572916
iter  70 value 82.194044
iter  80 value 81.843526
iter  90 value 81.493936
iter 100 value 81.257280
final  value 81.257280 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 116.745074 
iter  10 value 94.199885
iter  20 value 94.030225
iter  30 value 87.696455
iter  40 value 86.936629
iter  50 value 84.306870
iter  60 value 82.949390
iter  70 value 82.461700
iter  80 value 82.030415
iter  90 value 81.612982
iter 100 value 81.444967
final  value 81.444967 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 114.607841 
iter  10 value 94.017592
iter  20 value 90.676125
iter  30 value 84.740355
iter  40 value 84.289403
iter  50 value 83.875569
iter  60 value 82.634316
iter  70 value 82.191759
iter  80 value 82.142462
iter  90 value 82.006095
iter 100 value 81.959432
final  value 81.959432 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 112.359918 
iter  10 value 97.427405
iter  20 value 93.044972
iter  30 value 87.275315
iter  40 value 85.467974
iter  50 value 83.748193
iter  60 value 83.192672
iter  70 value 83.159401
iter  80 value 83.034644
iter  90 value 82.944710
iter 100 value 82.302186
final  value 82.302186 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.828345 
final  value 94.054761 
converged
Fitting Repeat 2 

# weights:  103
initial  value 109.752369 
final  value 94.054668 
converged
Fitting Repeat 3 

# weights:  103
initial  value 102.296579 
iter  10 value 94.054273
iter  20 value 94.018026
iter  30 value 85.067631
iter  40 value 85.061849
iter  50 value 85.059346
iter  60 value 85.049751
iter  70 value 85.010898
final  value 85.010879 
converged
Fitting Repeat 4 

# weights:  103
initial  value 100.003836 
final  value 94.054611 
converged
Fitting Repeat 5 

# weights:  103
initial  value 94.662225 
final  value 94.054481 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.223875 
iter  10 value 93.587593
iter  20 value 93.583615
iter  30 value 93.329625
iter  40 value 85.704858
final  value 85.608104 
converged
Fitting Repeat 2 

# weights:  305
initial  value 104.039308 
iter  10 value 94.056822
iter  20 value 93.850276
iter  30 value 86.611021
iter  40 value 84.941012
iter  50 value 84.079905
iter  50 value 84.079905
iter  50 value 84.079905
final  value 84.079905 
converged
Fitting Repeat 3 

# weights:  305
initial  value 103.764353 
iter  10 value 92.742079
iter  20 value 92.740516
iter  30 value 92.452304
iter  40 value 92.379184
iter  50 value 92.345201
iter  60 value 92.329481
iter  70 value 92.325272
iter  80 value 92.004415
iter  90 value 91.944782
final  value 91.943601 
converged
Fitting Repeat 4 

# weights:  305
initial  value 96.325595 
iter  10 value 93.587341
iter  20 value 93.582787
iter  30 value 93.503140
iter  40 value 85.734922
iter  50 value 85.733621
iter  60 value 85.732420
iter  70 value 84.536360
final  value 84.493042 
converged
Fitting Repeat 5 

# weights:  305
initial  value 107.697593 
iter  10 value 94.058165
iter  20 value 94.053333
iter  20 value 94.053333
iter  20 value 94.053333
final  value 94.053333 
converged
Fitting Repeat 1 

# weights:  507
initial  value 104.357159 
iter  10 value 94.060686
iter  20 value 93.032642
iter  30 value 85.878163
iter  40 value 85.741476
iter  50 value 85.738126
iter  60 value 85.717743
iter  70 value 83.271058
iter  80 value 81.883634
iter  90 value 81.709416
iter 100 value 81.699764
final  value 81.699764 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.740156 
iter  10 value 88.734919
iter  20 value 88.623769
iter  30 value 88.267944
iter  40 value 87.737932
iter  50 value 87.581900
iter  60 value 87.312924
iter  70 value 86.764399
iter  80 value 86.688247
iter  90 value 86.671743
iter 100 value 84.648694
final  value 84.648694 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 97.716430 
iter  10 value 93.590420
iter  20 value 93.520475
iter  30 value 86.019054
iter  40 value 81.873754
iter  50 value 80.839974
iter  60 value 80.155572
iter  70 value 79.886049
final  value 79.885974 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.265014 
iter  10 value 94.059822
iter  20 value 93.662360
iter  30 value 93.529328
final  value 93.529318 
converged
Fitting Repeat 5 

# weights:  507
initial  value 104.956157 
iter  10 value 93.590421
iter  20 value 93.583275
iter  30 value 91.848315
iter  40 value 87.210851
iter  50 value 83.080726
iter  60 value 82.021488
iter  70 value 81.695496
iter  80 value 81.694466
iter  90 value 81.694281
final  value 81.694085 
converged
Fitting Repeat 1 

# weights:  103
initial  value 96.557145 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.946175 
iter  10 value 91.596920
iter  20 value 90.206192
iter  30 value 90.204831
final  value 90.204782 
converged
Fitting Repeat 3 

# weights:  103
initial  value 96.530975 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.205567 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 98.263288 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  305
initial  value 97.343651 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  305
initial  value 99.541010 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  305
initial  value 95.045220 
iter  10 value 90.488290
final  value 90.428592 
converged
Fitting Repeat 4 

# weights:  305
initial  value 110.066609 
final  value 94.291892 
converged
Fitting Repeat 5 

# weights:  305
initial  value 102.664732 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  507
initial  value 105.727891 
final  value 94.455556 
converged
Fitting Repeat 2 

# weights:  507
initial  value 105.694459 
iter  10 value 92.516953
iter  20 value 89.756787
iter  30 value 89.600574
final  value 89.600566 
converged
Fitting Repeat 3 

# weights:  507
initial  value 111.855260 
final  value 94.484211 
converged
Fitting Repeat 4 

# weights:  507
initial  value 104.710757 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  507
initial  value 107.821172 
iter  10 value 94.141866
iter  20 value 93.073905
iter  30 value 93.064169
final  value 93.057083 
converged
Fitting Repeat 1 

# weights:  103
initial  value 97.462006 
iter  10 value 89.437128
iter  20 value 87.345333
iter  30 value 86.292518
iter  40 value 85.431699
final  value 85.419740 
converged
Fitting Repeat 2 

# weights:  103
initial  value 98.627257 
iter  10 value 94.518903
iter  20 value 94.487473
iter  30 value 93.828473
iter  40 value 89.044050
iter  50 value 87.034775
iter  60 value 86.086292
iter  70 value 85.501916
iter  80 value 84.975806
iter  90 value 84.657542
iter 100 value 84.643666
final  value 84.643666 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 98.071085 
iter  10 value 94.483511
iter  20 value 93.200534
iter  30 value 90.319788
iter  40 value 89.514030
iter  50 value 89.169166
iter  60 value 85.936885
iter  70 value 84.829004
iter  80 value 84.300365
iter  90 value 84.275112
iter 100 value 84.270907
final  value 84.270907 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 109.338075 
iter  10 value 94.346802
iter  20 value 88.290219
iter  30 value 87.171336
iter  40 value 86.100515
iter  50 value 85.515324
iter  60 value 85.213175
iter  70 value 85.146155
final  value 85.146144 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.509348 
iter  10 value 94.552725
iter  20 value 94.463484
iter  30 value 93.291695
iter  40 value 91.423524
iter  50 value 87.297269
iter  60 value 86.547649
iter  70 value 85.645572
iter  80 value 85.009043
iter  90 value 84.753513
final  value 84.753071 
converged
Fitting Repeat 1 

# weights:  305
initial  value 102.423015 
iter  10 value 94.140039
iter  20 value 91.054454
iter  30 value 85.757543
iter  40 value 84.787273
iter  50 value 84.314804
iter  60 value 84.138963
iter  70 value 83.453179
iter  80 value 82.566567
iter  90 value 81.943457
iter 100 value 81.571806
final  value 81.571806 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 105.808623 
iter  10 value 92.347182
iter  20 value 92.061722
iter  30 value 91.318579
iter  40 value 90.939019
iter  50 value 90.370440
iter  60 value 90.331254
iter  70 value 90.269722
iter  80 value 89.092647
iter  90 value 83.331852
iter 100 value 81.967792
final  value 81.967792 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 100.954468 
iter  10 value 94.825395
iter  20 value 94.518494
iter  30 value 94.098285
iter  40 value 90.947476
iter  50 value 90.883440
iter  60 value 90.695062
iter  70 value 87.130686
iter  80 value 86.196126
iter  90 value 85.115388
iter 100 value 83.824980
final  value 83.824980 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 105.846184 
iter  10 value 94.513246
iter  20 value 91.782843
iter  30 value 89.391673
iter  40 value 87.548935
iter  50 value 86.474944
iter  60 value 85.810080
iter  70 value 85.529003
iter  80 value 84.944243
iter  90 value 84.717917
iter 100 value 84.380651
final  value 84.380651 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 100.626462 
iter  10 value 94.512191
iter  20 value 90.875881
iter  30 value 86.753812
iter  40 value 85.391677
iter  50 value 84.855912
iter  60 value 83.779325
iter  70 value 81.727559
iter  80 value 81.180694
iter  90 value 81.057056
iter 100 value 80.869226
final  value 80.869226 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.703384 
iter  10 value 94.462946
iter  20 value 92.415227
iter  30 value 89.817057
iter  40 value 85.462089
iter  50 value 84.034572
iter  60 value 82.985022
iter  70 value 81.932481
iter  80 value 81.655772
iter  90 value 81.110091
iter 100 value 81.029147
final  value 81.029147 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 103.117114 
iter  10 value 93.803396
iter  20 value 91.555102
iter  30 value 90.358185
iter  40 value 89.905244
iter  50 value 86.981730
iter  60 value 85.211060
iter  70 value 84.291191
iter  80 value 83.184528
iter  90 value 83.011725
iter 100 value 82.941006
final  value 82.941006 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 112.039247 
iter  10 value 94.551128
iter  20 value 94.273399
iter  30 value 90.880553
iter  40 value 90.686652
iter  50 value 90.573502
iter  60 value 89.470982
iter  70 value 85.844558
iter  80 value 82.617225
iter  90 value 81.620271
iter 100 value 81.096418
final  value 81.096418 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 128.679930 
iter  10 value 94.816953
iter  20 value 90.716391
iter  30 value 90.320766
iter  40 value 90.052689
iter  50 value 87.743700
iter  60 value 84.593946
iter  70 value 83.989605
iter  80 value 83.775707
iter  90 value 83.575261
iter 100 value 83.239954
final  value 83.239954 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 111.556002 
iter  10 value 94.629700
iter  20 value 89.442519
iter  30 value 86.499819
iter  40 value 82.639723
iter  50 value 81.785834
iter  60 value 81.380786
iter  70 value 81.049501
iter  80 value 80.661382
iter  90 value 80.586571
iter 100 value 80.544192
final  value 80.544192 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 98.017143 
final  value 94.485627 
converged
Fitting Repeat 2 

# weights:  103
initial  value 96.199179 
final  value 94.486068 
converged
Fitting Repeat 3 

# weights:  103
initial  value 94.769613 
final  value 93.940791 
converged
Fitting Repeat 4 

# weights:  103
initial  value 98.555750 
final  value 94.485653 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.297039 
final  value 94.486129 
converged
Fitting Repeat 1 

# weights:  305
initial  value 116.501621 
iter  10 value 94.296850
final  value 94.296272 
converged
Fitting Repeat 2 

# weights:  305
initial  value 132.091741 
iter  10 value 94.488988
iter  20 value 94.484193
iter  30 value 93.928552
iter  40 value 91.705420
iter  50 value 91.687967
iter  60 value 91.687196
final  value 91.686915 
converged
Fitting Repeat 3 

# weights:  305
initial  value 96.004967 
iter  10 value 94.486984
iter  20 value 94.464857
iter  30 value 94.294348
iter  40 value 93.941921
iter  50 value 89.156075
iter  60 value 88.180993
final  value 88.124238 
converged
Fitting Repeat 4 

# weights:  305
initial  value 98.566910 
iter  10 value 94.306240
iter  20 value 94.296824
iter  30 value 94.283982
iter  40 value 86.253360
iter  50 value 85.345017
iter  60 value 85.339789
iter  70 value 85.018704
iter  80 value 85.014489
final  value 85.014405 
converged
Fitting Repeat 5 

# weights:  305
initial  value 99.933721 
iter  10 value 94.488712
iter  20 value 93.658464
iter  30 value 90.229889
iter  40 value 85.901566
iter  50 value 85.808941
iter  60 value 83.147344
iter  70 value 82.140433
iter  80 value 82.131386
iter  90 value 82.128324
iter 100 value 82.117662
final  value 82.117662 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 100.623274 
iter  10 value 94.300059
iter  20 value 94.292221
final  value 94.292169 
converged
Fitting Repeat 2 

# weights:  507
initial  value 104.162142 
iter  10 value 94.264324
iter  20 value 94.259495
iter  30 value 94.256726
iter  30 value 94.256726
iter  30 value 94.256726
final  value 94.256726 
converged
Fitting Repeat 3 

# weights:  507
initial  value 98.432907 
iter  10 value 94.490971
iter  20 value 93.031543
iter  30 value 88.936918
iter  40 value 88.744427
iter  50 value 88.740305
iter  60 value 87.453404
iter  70 value 83.124156
iter  80 value 83.017909
iter  90 value 83.007808
iter 100 value 82.993687
final  value 82.993687 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 113.782466 
iter  10 value 90.610949
iter  20 value 84.742460
iter  30 value 84.676805
iter  40 value 84.430873
iter  50 value 84.417790
iter  60 value 84.238335
iter  70 value 83.262761
iter  80 value 82.760122
iter  90 value 82.355248
iter 100 value 81.813680
final  value 81.813680 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 99.827898 
iter  10 value 91.236052
iter  20 value 90.624862
iter  30 value 90.615374
final  value 90.614572 
converged
Fitting Repeat 1 

# weights:  103
initial  value 109.083641 
final  value 94.484211 
converged
Fitting Repeat 2 

# weights:  103
initial  value 107.240936 
final  value 94.484211 
converged
Fitting Repeat 3 

# weights:  103
initial  value 98.412226 
iter  10 value 93.283769
iter  20 value 83.962721
iter  30 value 82.218600
iter  40 value 82.218329
final  value 82.218018 
converged
Fitting Repeat 4 

# weights:  103
initial  value 103.113820 
final  value 94.484211 
converged
Fitting Repeat 5 

# weights:  103
initial  value 96.724319 
final  value 93.772973 
converged
Fitting Repeat 1 

# weights:  305
initial  value 99.943855 
iter  10 value 93.822256
final  value 93.772973 
converged
Fitting Repeat 2 

# weights:  305
initial  value 101.786673 
iter  10 value 87.579508
iter  20 value 85.426541
iter  30 value 80.976233
iter  40 value 78.937465
iter  50 value 78.486471
iter  60 value 78.133290
iter  70 value 78.123729
iter  80 value 78.105251
iter  90 value 78.071200
iter 100 value 78.030795
final  value 78.030795 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 102.371913 
iter  10 value 94.484313
iter  20 value 93.780319
iter  30 value 93.774833
final  value 93.772973 
converged
Fitting Repeat 4 

# weights:  305
initial  value 103.547793 
iter  10 value 93.766151
iter  20 value 92.124317
iter  30 value 91.967045
iter  30 value 91.967044
iter  30 value 91.967044
final  value 91.967044 
converged
Fitting Repeat 5 

# weights:  305
initial  value 97.732808 
final  value 93.701657 
converged
Fitting Repeat 1 

# weights:  507
initial  value 100.713754 
iter  10 value 91.482445
final  value 91.480568 
converged
Fitting Repeat 2 

# weights:  507
initial  value 99.903740 
iter  10 value 93.772975
final  value 93.772973 
converged
Fitting Repeat 3 

# weights:  507
initial  value 96.352478 
final  value 94.448052 
converged
Fitting Repeat 4 

# weights:  507
initial  value 96.683452 
iter  10 value 93.750754
iter  20 value 93.720969
final  value 93.720301 
converged
Fitting Repeat 5 

# weights:  507
initial  value 115.317953 
final  value 94.484211 
converged
Fitting Repeat 1 

# weights:  103
initial  value 110.009961 
iter  10 value 94.458646
iter  20 value 86.568603
iter  30 value 85.769847
iter  40 value 85.553825
iter  50 value 83.209407
iter  60 value 82.192176
iter  70 value 82.023624
iter  80 value 81.907910
final  value 81.904632 
converged
Fitting Repeat 2 

# weights:  103
initial  value 101.548008 
iter  10 value 94.488612
iter  10 value 94.488612
iter  20 value 94.289677
iter  30 value 94.108689
iter  40 value 93.938068
iter  50 value 92.747616
iter  60 value 83.935470
iter  70 value 82.856262
iter  80 value 82.389275
iter  90 value 82.344909
iter 100 value 82.208673
final  value 82.208673 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  103
initial  value 99.799205 
iter  10 value 94.489279
iter  20 value 94.427009
iter  30 value 86.092300
iter  40 value 85.701812
iter  50 value 84.179382
iter  60 value 83.699340
iter  70 value 81.947980
iter  80 value 81.010490
iter  90 value 80.328168
iter 100 value 79.932743
final  value 79.932743 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  103
initial  value 97.580735 
iter  10 value 94.499580
iter  20 value 87.862834
iter  30 value 83.320174
iter  40 value 82.522521
iter  50 value 81.991556
iter  60 value 81.631765
iter  70 value 81.480577
final  value 81.480049 
converged
Fitting Repeat 5 

# weights:  103
initial  value 104.057938 
iter  10 value 94.728999
iter  20 value 94.499508
iter  30 value 94.486311
iter  40 value 93.984598
iter  50 value 93.976186
iter  60 value 93.956037
iter  70 value 87.604454
iter  80 value 84.355755
iter  90 value 82.149257
iter 100 value 80.854472
final  value 80.854472 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  305
initial  value 103.639235 
iter  10 value 94.453092
iter  20 value 92.891591
iter  30 value 85.827408
iter  40 value 84.073764
iter  50 value 81.486170
iter  60 value 80.247325
iter  70 value 79.628983
iter  80 value 79.533734
iter  90 value 79.445654
iter 100 value 79.373605
final  value 79.373605 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 116.491370 
iter  10 value 94.428453
iter  20 value 92.317643
iter  30 value 91.142698
iter  40 value 90.993002
iter  50 value 84.222750
iter  60 value 82.102574
iter  70 value 80.571043
iter  80 value 80.095055
iter  90 value 79.918043
iter 100 value 79.826718
final  value 79.826718 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  305
initial  value 117.439368 
iter  10 value 93.965183
iter  20 value 92.944290
iter  30 value 87.650477
iter  40 value 85.679440
iter  50 value 84.175653
iter  60 value 82.589092
iter  70 value 82.034506
iter  80 value 81.861655
iter  90 value 81.713980
iter 100 value 79.771467
final  value 79.771467 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  305
initial  value 100.029428 
iter  10 value 93.861652
iter  20 value 84.614902
iter  30 value 82.010984
iter  40 value 80.489409
iter  50 value 79.703202
iter  60 value 79.080392
iter  70 value 78.544362
iter  80 value 78.506616
iter  90 value 78.456357
iter 100 value 78.336130
final  value 78.336130 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  305
initial  value 111.225974 
iter  10 value 94.504849
iter  20 value 94.406966
iter  30 value 94.016500
iter  40 value 85.291943
iter  50 value 83.415318
iter  60 value 83.006326
iter  70 value 81.171771
iter  80 value 80.000115
iter  90 value 79.532733
iter 100 value 79.480641
final  value 79.480641 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 103.672954 
iter  10 value 94.037468
iter  20 value 88.451822
iter  30 value 85.762624
iter  40 value 85.142509
iter  50 value 82.853060
iter  60 value 82.235952
iter  70 value 81.700638
iter  80 value 81.480675
iter  90 value 81.090876
iter 100 value 79.802569
final  value 79.802569 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 126.943965 
iter  10 value 94.487719
iter  20 value 94.118900
iter  30 value 88.190361
iter  40 value 83.240198
iter  50 value 82.772897
iter  60 value 82.381531
iter  70 value 81.914394
iter  80 value 79.542960
iter  90 value 78.740170
iter 100 value 78.503978
final  value 78.503978 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 110.189140 
iter  10 value 95.765125
iter  20 value 94.520350
iter  30 value 84.909618
iter  40 value 83.347066
iter  50 value 83.043925
iter  60 value 82.150393
iter  70 value 80.505635
iter  80 value 79.575748
iter  90 value 78.129635
iter 100 value 77.923344
final  value 77.923344 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 104.481175 
iter  10 value 94.298954
iter  20 value 94.046965
iter  30 value 93.909592
iter  40 value 93.080280
iter  50 value 88.347673
iter  60 value 84.098989
iter  70 value 81.720267
iter  80 value 80.980075
iter  90 value 80.776793
iter 100 value 79.546411
final  value 79.546411 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 109.190338 
iter  10 value 86.078863
iter  20 value 80.133438
iter  30 value 79.071575
iter  40 value 78.551013
iter  50 value 77.915030
iter  60 value 77.790143
iter  70 value 77.712000
iter  80 value 77.439851
iter  90 value 77.342544
iter 100 value 77.294032
final  value 77.294032 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  103
initial  value 95.293210 
final  value 94.485953 
converged
Fitting Repeat 2 

# weights:  103
initial  value 99.857852 
final  value 94.485953 
converged
Fitting Repeat 3 

# weights:  103
initial  value 101.037784 
final  value 94.486046 
converged
Fitting Repeat 4 

# weights:  103
initial  value 95.237207 
final  value 94.485811 
converged
Fitting Repeat 5 

# weights:  103
initial  value 99.268824 
final  value 94.485893 
converged
Fitting Repeat 1 

# weights:  305
initial  value 107.656159 
iter  10 value 94.489486
iter  20 value 93.998899
iter  30 value 85.423916
iter  40 value 84.125294
iter  50 value 83.027562
iter  60 value 78.196709
iter  70 value 78.052511
iter  80 value 78.046773
iter  90 value 78.027533
iter 100 value 77.752638
final  value 77.752638 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  305
initial  value 99.129661 
iter  10 value 94.218858
iter  20 value 93.795561
iter  30 value 86.171201
iter  40 value 84.542555
iter  50 value 84.509124
iter  60 value 84.434112
iter  70 value 84.398329
final  value 84.398248 
converged
Fitting Repeat 3 

# weights:  305
initial  value 108.347185 
iter  10 value 82.807918
iter  20 value 82.318028
iter  30 value 82.242372
iter  40 value 81.437543
iter  50 value 81.315585
final  value 81.315582 
converged
Fitting Repeat 4 

# weights:  305
initial  value 102.674294 
iter  10 value 89.161995
iter  20 value 86.522059
final  value 86.518585 
converged
Fitting Repeat 5 

# weights:  305
initial  value 96.940447 
iter  10 value 94.453029
iter  20 value 94.448217
iter  30 value 93.226189
iter  40 value 85.004067
iter  50 value 84.989796
iter  60 value 84.962551
iter  70 value 84.670325
iter  80 value 84.583619
iter  90 value 84.570656
iter 100 value 83.738606
final  value 83.738606 
stopped after 100 iterations
Fitting Repeat 1 

# weights:  507
initial  value 107.960507 
iter  10 value 93.784037
iter  20 value 93.782197
iter  30 value 93.020048
iter  40 value 91.528848
iter  50 value 85.310120
iter  60 value 84.056405
iter  70 value 84.055542
iter  80 value 84.054142
iter  90 value 83.732002
iter 100 value 81.759461
final  value 81.759461 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 115.917045 
iter  10 value 94.113984
iter  20 value 94.108259
iter  30 value 93.717650
iter  40 value 87.198342
iter  50 value 82.101652
iter  60 value 81.565837
iter  70 value 81.552186
final  value 81.552036 
converged
Fitting Repeat 3 

# weights:  507
initial  value 103.232575 
iter  10 value 93.291866
iter  20 value 85.371469
iter  30 value 85.256647
iter  40 value 84.139580
iter  50 value 83.696421
iter  60 value 83.613778
iter  70 value 83.612197
iter  80 value 83.609428
iter  90 value 83.481059
iter 100 value 83.456393
final  value 83.456393 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 94.919477 
iter  10 value 93.649189
iter  20 value 93.628325
iter  30 value 93.626645
iter  40 value 93.565680
iter  50 value 93.557954
final  value 93.557899 
converged
Fitting Repeat 5 

# weights:  507
initial  value 97.872622 
iter  10 value 94.487365
iter  20 value 94.484724
iter  30 value 94.484520
iter  30 value 94.484520
iter  30 value 94.484520
final  value 94.484520 
converged
Fitting Repeat 1 

# weights:  507
initial  value 129.427406 
iter  10 value 117.830400
iter  20 value 108.215892
iter  30 value 105.820177
iter  40 value 105.187131
iter  50 value 103.089761
iter  60 value 102.245819
iter  70 value 101.630703
iter  80 value 101.415993
iter  90 value 100.643403
iter 100 value 100.497303
final  value 100.497303 
stopped after 100 iterations
Fitting Repeat 2 

# weights:  507
initial  value 130.336630 
iter  10 value 114.250230
iter  20 value 109.443811
iter  30 value 108.440170
iter  40 value 106.454521
iter  50 value 105.038844
iter  60 value 102.893169
iter  70 value 102.627673
iter  80 value 102.324975
iter  90 value 101.973030
iter 100 value 101.834463
final  value 101.834463 
stopped after 100 iterations
Fitting Repeat 3 

# weights:  507
initial  value 128.580138 
iter  10 value 117.967453
iter  20 value 108.102289
iter  30 value 106.527972
iter  40 value 104.333989
iter  50 value 103.720528
iter  60 value 103.164592
iter  70 value 102.903146
iter  80 value 102.482591
iter  90 value 101.576098
iter 100 value 101.213338
final  value 101.213338 
stopped after 100 iterations
Fitting Repeat 4 

# weights:  507
initial  value 157.125226 
iter  10 value 117.249351
iter  20 value 114.533827
iter  30 value 114.052928
iter  40 value 111.561275
iter  50 value 107.082568
iter  60 value 104.817802
iter  70 value 104.383296
iter  80 value 104.050925
iter  90 value 103.702283
iter 100 value 103.138758
final  value 103.138758 
stopped after 100 iterations
Fitting Repeat 5 

# weights:  507
initial  value 141.749651 
iter  10 value 119.533576
iter  20 value 108.923423
iter  30 value 106.091437
iter  40 value 105.554125
iter  50 value 103.490161
iter  60 value 103.038788
iter  70 value 102.723269
iter  80 value 102.141440
iter  90 value 101.756262
iter 100 value 101.641881
final  value 101.641881 
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 04:30:34 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 
  45.34    1.96   46.87 

Example timings

HPiP.Rcheck/HPiP-Ex.timings

nameusersystemelapsed
FSmethod32.00 2.1434.22
FreqInteractors0.250.010.28
calculateAAC0.060.000.06
calculateAutocor0.410.190.59
calculateCTDC0.110.000.11
calculateCTDD0.570.060.64
calculateCTDT0.360.040.39
calculateCTriad0.490.060.55
calculateDC0.140.000.14
calculateF0.360.010.37
calculateKSAAP0.140.020.15
calculateQD_Sm1.850.202.05
calculateTC1.390.231.63
calculateTC_Sm0.290.020.31
corr_plot29.71 2.0331.73
enrichfindP 0.58 0.2217.82
enrichfind_hp0.120.001.09
enrichplot0.450.000.45
filter_missing_values000
getFASTA0.020.002.14
getHPI000
get_negativePPI000
get_positivePPI000
impute_missing_data000
plotPPI0.060.000.09
pred_ensembel14.25 0.6410.69
var_imp31.13 1.3032.44