Matineh Rahmatbakhsh
| Snapshot Date: 2024-03-27 14:05:05 -0400 (Wed, 27 Mar 2024) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_18 |
| git_last_commit: 677208a |
| git_last_commit_date: 2023-10-24 11:36:21 -0400 (Tue, 24 Oct 2023) |
| Back to Multiple platform build/check report for BioC 3.18: simplified long |
|
This page was generated on 2024-03-29 11:36:52 -0400 (Fri, 29 Mar 2024).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4669 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.3.3 (2024-02-29 ucrt) -- "Angel Food Cake" | 4404 |
| merida1 | macOS 12.7.1 Monterey | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4427 |
| 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 974/2266 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.8.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 22.04.3 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino4 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.1 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson1 | macOS 13.6.1 Ventura / arm64 | see weekly results here | ||||||||||||
|
To the developers/maintainers of the HPiP package: - Allow up to 24 hours (and sometimes 48 hours) for your latest push to git@git.bioconductor.org:packages/HPiP.git to reflect on this report. See Troubleshooting Build Report for more information. - Use the following Renviron settings to reproduce errors and warnings. - If 'R CMD check' started to fail recently on the Linux builder(s) over a missing dependency, add the missing dependency to 'Suggests:' in your DESCRIPTION file. See Renviron.bioc for more information. |
| Package: HPiP |
| Version: 1.8.0 |
| Command: F:\biocbuild\bbs-3.18-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.18-bioc\R\library --no-vignettes --timings HPiP_1.8.0.tar.gz |
| StartedAt: 2024-03-28 01:47:00 -0400 (Thu, 28 Mar 2024) |
| EndedAt: 2024-03-28 01:51:46 -0400 (Thu, 28 Mar 2024) |
| EllapsedTime: 285.7 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.18-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.18-bioc\R\library --no-vignettes --timings HPiP_1.8.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck'
* using R version 4.3.3 (2024-02-29 ucrt)
* using platform: x86_64-w64-mingw32 (64-bit)
* R was compiled by
gcc.exe (GCC) 12.3.0
GNU Fortran (GCC) 12.3.0
* 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 '1.8.0'
* 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 ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking R 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 ... OK
* 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 32.59 1.14 33.75
FSmethod 31.78 1.20 33.07
corr_plot 31.30 0.97 32.28
pred_ensembel 13.30 0.59 10.23
enrichfindP 0.58 0.05 14.31
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in 'inst/doc' ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
'F:/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.18-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.18-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)
HPiP.Rcheck/tests/runTests.Rout
R version 4.3.3 (2024-02-29 ucrt) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
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 98.885816
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 99.239999
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 98.751323
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.452176
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 98.723772
iter 10 value 94.443247
final value 94.443243
converged
Fitting Repeat 1
# weights: 305
initial value 95.433727
final value 94.466823
converged
Fitting Repeat 2
# weights: 305
initial value 101.483644
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 99.575973
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 98.691199
iter 10 value 90.632085
iter 20 value 88.728133
iter 30 value 88.726316
final value 88.726314
converged
Fitting Repeat 5
# weights: 305
initial value 97.861136
iter 10 value 94.428926
final value 94.428840
converged
Fitting Repeat 1
# weights: 507
initial value 112.483502
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 118.966201
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 97.513499
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 99.677166
iter 10 value 84.218850
iter 20 value 81.983031
final value 81.983007
converged
Fitting Repeat 5
# weights: 507
initial value 108.437547
iter 10 value 94.499969
iter 20 value 88.047087
iter 30 value 83.265416
iter 40 value 81.091677
iter 50 value 80.729392
iter 60 value 79.738433
iter 70 value 79.164210
iter 80 value 78.515959
iter 90 value 78.500163
iter 100 value 78.498010
final value 78.498010
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.587249
iter 10 value 94.461477
iter 20 value 94.175475
iter 30 value 89.841756
iter 40 value 88.475201
iter 50 value 88.275317
iter 60 value 81.634564
iter 70 value 80.765892
iter 80 value 80.446538
iter 90 value 80.349506
iter 100 value 79.205383
final value 79.205383
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 96.805445
iter 10 value 94.489328
iter 20 value 94.477415
iter 30 value 92.405485
iter 40 value 88.012987
iter 50 value 84.179788
iter 60 value 83.924148
iter 70 value 83.780448
iter 80 value 82.237421
iter 90 value 81.710115
final value 81.650556
converged
Fitting Repeat 3
# weights: 103
initial value 97.589769
iter 10 value 94.464440
iter 20 value 94.096214
iter 30 value 90.073471
iter 40 value 84.705869
iter 50 value 83.395275
iter 60 value 82.088842
iter 70 value 81.727161
iter 80 value 81.018564
iter 90 value 80.691233
iter 100 value 80.612917
final value 80.612917
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 101.050940
iter 10 value 92.501317
iter 20 value 86.008847
iter 30 value 81.615688
iter 40 value 80.777125
iter 50 value 80.368339
iter 60 value 80.241733
iter 70 value 78.862017
iter 80 value 78.609937
iter 90 value 78.382820
iter 100 value 78.271425
final value 78.271425
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 105.408880
iter 10 value 94.965280
iter 20 value 94.485200
iter 30 value 93.165017
iter 40 value 87.290903
iter 50 value 84.792303
iter 60 value 84.040183
iter 70 value 83.259354
iter 80 value 82.894652
iter 90 value 82.164625
final value 82.120903
converged
Fitting Repeat 1
# weights: 305
initial value 105.396725
iter 10 value 94.076174
iter 20 value 84.798495
iter 30 value 83.831885
iter 40 value 83.113129
iter 50 value 81.298465
iter 60 value 78.901981
iter 70 value 77.610733
iter 80 value 77.196372
iter 90 value 77.000873
iter 100 value 76.942850
final value 76.942850
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.429706
iter 10 value 88.108765
iter 20 value 87.211011
iter 30 value 86.404321
iter 40 value 85.631834
iter 50 value 82.782026
iter 60 value 79.217130
iter 70 value 78.330904
iter 80 value 77.627849
iter 90 value 77.444487
iter 100 value 77.350435
final value 77.350435
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 122.088886
iter 10 value 94.762017
iter 20 value 85.666058
iter 30 value 83.977767
iter 40 value 81.569308
iter 50 value 79.095262
iter 60 value 78.767910
iter 70 value 78.624293
iter 80 value 78.262626
iter 90 value 78.095945
iter 100 value 77.070366
final value 77.070366
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 122.331617
iter 10 value 93.176419
iter 20 value 80.717930
iter 30 value 80.331263
iter 40 value 80.176048
iter 50 value 80.114086
iter 60 value 78.978099
iter 70 value 78.562349
iter 80 value 78.457336
iter 90 value 77.990511
iter 100 value 77.939519
final value 77.939519
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 112.532058
iter 10 value 94.519137
iter 20 value 88.367385
iter 30 value 87.761883
iter 40 value 86.696728
iter 50 value 82.742739
iter 60 value 81.549627
iter 70 value 79.400052
iter 80 value 77.960127
iter 90 value 77.597569
iter 100 value 77.138334
final value 77.138334
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.016433
iter 10 value 94.603266
iter 20 value 92.449583
iter 30 value 86.582620
iter 40 value 80.977983
iter 50 value 79.794288
iter 60 value 78.694090
iter 70 value 77.784701
iter 80 value 77.392678
iter 90 value 77.262518
iter 100 value 77.244244
final value 77.244244
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 139.385494
iter 10 value 94.499244
iter 20 value 93.858062
iter 30 value 83.889864
iter 40 value 81.353920
iter 50 value 79.773764
iter 60 value 79.435401
iter 70 value 79.175371
iter 80 value 76.979984
iter 90 value 76.598472
iter 100 value 76.442290
final value 76.442290
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 114.401983
iter 10 value 98.710187
iter 20 value 84.638068
iter 30 value 81.327069
iter 40 value 81.128470
iter 50 value 80.747942
iter 60 value 79.085174
iter 70 value 78.726032
iter 80 value 78.539871
iter 90 value 78.366327
iter 100 value 78.213026
final value 78.213026
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.347734
iter 10 value 94.485778
iter 20 value 91.063311
iter 30 value 88.455268
iter 40 value 83.969494
iter 50 value 82.966787
iter 60 value 81.902402
iter 70 value 81.287993
iter 80 value 79.368554
iter 90 value 79.181984
iter 100 value 79.033819
final value 79.033819
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.705207
iter 10 value 94.838209
iter 20 value 94.512427
iter 30 value 94.250796
iter 40 value 91.122927
iter 50 value 89.464795
iter 60 value 87.303889
iter 70 value 86.717441
iter 80 value 86.450884
iter 90 value 84.695156
iter 100 value 79.710786
final value 79.710786
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.096254
final value 94.485941
converged
Fitting Repeat 2
# weights: 103
initial value 95.698823
final value 94.485959
converged
Fitting Repeat 3
# weights: 103
initial value 102.686224
final value 94.485843
converged
Fitting Repeat 4
# weights: 103
initial value 97.533914
iter 10 value 94.485629
iter 20 value 94.426808
iter 30 value 82.153126
iter 40 value 80.320193
final value 80.320189
converged
Fitting Repeat 5
# weights: 103
initial value 99.969283
final value 94.485862
converged
Fitting Repeat 1
# weights: 305
initial value 108.707359
iter 10 value 94.489671
iter 20 value 94.484269
iter 30 value 93.264750
iter 40 value 82.855779
iter 50 value 82.806115
iter 60 value 82.805892
iter 70 value 82.805703
iter 80 value 82.804992
iter 90 value 80.341981
iter 100 value 77.361403
final value 77.361403
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 96.970401
iter 10 value 94.488521
iter 20 value 94.448790
iter 30 value 94.265332
iter 30 value 94.265331
iter 30 value 94.265331
final value 94.265331
converged
Fitting Repeat 3
# weights: 305
initial value 101.790410
iter 10 value 94.490965
iter 20 value 94.488408
iter 30 value 93.963028
iter 40 value 89.816580
iter 50 value 89.667008
iter 60 value 84.212664
iter 70 value 84.200075
iter 80 value 84.197073
iter 90 value 83.340672
iter 100 value 82.758589
final value 82.758589
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.281142
iter 10 value 94.448903
iter 20 value 94.388419
iter 30 value 86.575935
iter 40 value 86.405437
iter 50 value 86.123276
final value 86.122891
converged
Fitting Repeat 5
# weights: 305
initial value 96.193546
iter 10 value 94.471390
iter 20 value 93.795511
iter 30 value 89.809503
iter 40 value 84.791937
iter 50 value 83.732207
iter 60 value 83.654303
iter 70 value 83.430942
iter 80 value 83.429371
final value 83.429369
converged
Fitting Repeat 1
# weights: 507
initial value 110.997853
iter 10 value 91.529895
iter 20 value 86.965088
iter 30 value 85.645152
iter 40 value 85.641614
iter 50 value 85.637132
iter 60 value 85.636947
final value 85.636722
converged
Fitting Repeat 2
# weights: 507
initial value 95.116779
iter 10 value 88.178951
iter 20 value 84.373200
iter 30 value 83.915643
iter 40 value 83.339541
iter 50 value 83.156559
final value 83.154528
converged
Fitting Repeat 3
# weights: 507
initial value 100.534725
iter 10 value 94.223452
iter 10 value 94.223452
iter 10 value 94.223452
final value 94.223452
converged
Fitting Repeat 4
# weights: 507
initial value 98.637500
iter 10 value 94.490876
iter 20 value 87.104773
iter 30 value 80.053722
iter 40 value 79.291809
iter 50 value 75.503833
iter 60 value 75.332684
iter 70 value 75.322457
iter 80 value 75.281643
iter 90 value 75.249931
iter 100 value 75.122841
final value 75.122841
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 96.822719
iter 10 value 94.475197
iter 20 value 94.455405
iter 30 value 89.024440
iter 40 value 86.536399
iter 50 value 85.583803
iter 60 value 84.785971
iter 70 value 84.405300
iter 80 value 83.046520
iter 90 value 81.530819
iter 100 value 78.571744
final value 78.571744
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 95.998947
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 99.009280
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 95.026324
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 101.945087
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 96.237489
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 135.525601
iter 10 value 94.389989
final value 94.353555
converged
Fitting Repeat 2
# weights: 305
initial value 104.032857
final value 94.353550
converged
Fitting Repeat 3
# weights: 305
initial value 100.222824
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 95.151027
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 118.890466
iter 10 value 94.320299
iter 10 value 94.320299
iter 10 value 94.320299
final value 94.320299
converged
Fitting Repeat 1
# weights: 507
initial value 117.515744
iter 10 value 90.123482
iter 20 value 89.371423
iter 30 value 89.356065
iter 40 value 88.159231
iter 50 value 87.745812
iter 60 value 87.744831
iter 70 value 87.744517
final value 87.744514
converged
Fitting Repeat 2
# weights: 507
initial value 129.942044
iter 10 value 93.949925
iter 20 value 88.687703
final value 88.182955
converged
Fitting Repeat 3
# weights: 507
initial value 116.215039
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 95.583853
final value 94.354396
converged
Fitting Repeat 5
# weights: 507
initial value 99.739279
final value 94.354396
converged
Fitting Repeat 1
# weights: 103
initial value 98.184153
iter 10 value 94.488640
iter 20 value 89.354120
iter 30 value 87.111879
iter 40 value 86.909609
iter 50 value 86.752361
iter 60 value 86.621618
iter 70 value 86.492074
iter 80 value 86.390481
final value 86.387390
converged
Fitting Repeat 2
# weights: 103
initial value 97.053761
iter 10 value 94.526723
iter 20 value 94.485164
iter 30 value 94.449070
iter 40 value 94.195044
iter 50 value 94.186585
iter 60 value 94.183359
iter 70 value 87.236288
iter 80 value 84.651743
iter 90 value 84.132392
iter 100 value 83.806002
final value 83.806002
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 103.426742
iter 10 value 94.448386
iter 20 value 94.113492
iter 30 value 93.394676
iter 40 value 87.587791
iter 50 value 87.121806
iter 60 value 86.673977
iter 70 value 86.580205
iter 80 value 86.412366
iter 90 value 86.387460
final value 86.387390
converged
Fitting Repeat 4
# weights: 103
initial value 99.952189
iter 10 value 94.418253
iter 20 value 87.109174
iter 30 value 84.338052
iter 40 value 83.531852
iter 50 value 83.341723
iter 60 value 83.220951
iter 70 value 82.999929
iter 80 value 82.972491
iter 80 value 82.972490
iter 80 value 82.972490
final value 82.972490
converged
Fitting Repeat 5
# weights: 103
initial value 100.117462
iter 10 value 94.474052
iter 20 value 86.076879
iter 30 value 84.530815
iter 40 value 84.096184
iter 50 value 83.522211
iter 60 value 83.121939
iter 70 value 83.032794
iter 80 value 82.973948
final value 82.972490
converged
Fitting Repeat 1
# weights: 305
initial value 102.460940
iter 10 value 94.230286
iter 20 value 91.679287
iter 30 value 91.360368
iter 40 value 86.696613
iter 50 value 84.748789
iter 60 value 84.554935
iter 70 value 83.906048
iter 80 value 83.578374
iter 90 value 83.247372
iter 100 value 82.707299
final value 82.707299
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 100.092113
iter 10 value 93.098381
iter 20 value 87.517291
iter 30 value 86.645116
iter 40 value 86.432541
iter 50 value 86.257776
iter 60 value 86.218183
iter 70 value 86.199160
iter 80 value 85.930002
iter 90 value 85.545174
iter 100 value 85.512915
final value 85.512915
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.128174
iter 10 value 94.638301
iter 20 value 94.413728
iter 30 value 88.121375
iter 40 value 85.734975
iter 50 value 82.892975
iter 60 value 82.700449
iter 70 value 82.374876
iter 80 value 82.278485
iter 90 value 82.260036
iter 100 value 82.074632
final value 82.074632
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 117.955828
iter 10 value 94.604754
iter 20 value 94.142592
iter 30 value 86.948365
iter 40 value 85.977857
iter 50 value 85.490074
iter 60 value 85.055605
iter 70 value 84.986534
iter 80 value 84.458515
iter 90 value 83.052803
iter 100 value 82.660802
final value 82.660802
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.932334
iter 10 value 94.664006
iter 20 value 93.670267
iter 30 value 93.404441
iter 40 value 86.100868
iter 50 value 85.076090
iter 60 value 83.952998
iter 70 value 83.273438
iter 80 value 83.031199
iter 90 value 82.821329
iter 100 value 82.644043
final value 82.644043
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 142.591683
iter 10 value 94.429161
iter 20 value 88.790099
iter 30 value 85.173349
iter 40 value 84.250026
iter 50 value 84.113161
iter 60 value 83.793008
iter 70 value 83.224437
iter 80 value 82.487984
iter 90 value 82.267602
iter 100 value 82.157874
final value 82.157874
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 109.922152
iter 10 value 92.418566
iter 20 value 91.533932
iter 30 value 90.679002
iter 40 value 89.808995
iter 50 value 88.659015
iter 60 value 88.396148
iter 70 value 87.658448
iter 80 value 84.873982
iter 90 value 84.291011
iter 100 value 83.747525
final value 83.747525
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 121.672357
iter 10 value 94.451119
iter 20 value 90.910686
iter 30 value 85.936374
iter 40 value 83.681894
iter 50 value 82.734434
iter 60 value 82.488531
iter 70 value 82.130023
iter 80 value 81.751159
iter 90 value 81.521562
iter 100 value 81.456739
final value 81.456739
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 129.130063
iter 10 value 94.575143
iter 20 value 93.929469
iter 30 value 91.439049
iter 40 value 90.492519
iter 50 value 90.288568
iter 60 value 89.863514
iter 70 value 86.401448
iter 80 value 84.388939
iter 90 value 83.640682
iter 100 value 83.180995
final value 83.180995
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.770676
iter 10 value 94.048286
iter 20 value 88.776728
iter 30 value 86.511804
iter 40 value 86.025547
iter 50 value 85.625297
iter 60 value 85.030512
iter 70 value 83.451463
iter 80 value 82.695270
iter 90 value 82.583925
iter 100 value 82.252642
final value 82.252642
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 104.968043
final value 94.356267
converged
Fitting Repeat 2
# weights: 103
initial value 96.529522
final value 94.485577
converged
Fitting Repeat 3
# weights: 103
initial value 96.398594
final value 94.389133
converged
Fitting Repeat 4
# weights: 103
initial value 97.730014
iter 10 value 91.857758
iter 20 value 91.147403
iter 30 value 91.140442
iter 40 value 91.140345
iter 50 value 91.140055
iter 60 value 91.139663
iter 70 value 91.139318
iter 80 value 85.392316
iter 90 value 85.064163
iter 100 value 85.021573
final value 85.021573
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 99.279739
final value 94.387031
converged
Fitting Repeat 1
# weights: 305
initial value 96.011486
iter 10 value 94.359450
iter 20 value 94.354907
final value 94.354564
converged
Fitting Repeat 2
# weights: 305
initial value 97.829735
iter 10 value 94.488835
iter 20 value 89.029201
iter 30 value 88.884193
iter 40 value 87.938379
final value 87.875504
converged
Fitting Repeat 3
# weights: 305
initial value 96.828558
iter 10 value 94.432677
iter 20 value 94.311179
iter 30 value 94.255118
iter 40 value 94.054035
iter 50 value 94.049848
final value 94.049808
converged
Fitting Repeat 4
# weights: 305
initial value 97.113319
iter 10 value 94.488442
iter 20 value 94.460088
iter 30 value 93.668696
iter 40 value 86.067221
iter 50 value 85.923486
iter 60 value 85.678433
iter 70 value 82.994130
iter 80 value 82.733967
iter 90 value 82.149726
iter 100 value 81.532639
final value 81.532639
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 96.892947
iter 10 value 94.359571
iter 20 value 94.354858
iter 30 value 92.444761
iter 40 value 91.430081
iter 50 value 91.319244
iter 60 value 90.988527
final value 90.961831
converged
Fitting Repeat 1
# weights: 507
initial value 105.630970
iter 10 value 93.709563
iter 20 value 93.703143
iter 30 value 93.415797
iter 40 value 86.483978
iter 50 value 86.297876
iter 60 value 85.867136
iter 70 value 85.559705
iter 80 value 85.286410
iter 90 value 85.066631
iter 100 value 85.065297
final value 85.065297
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 113.725655
iter 10 value 94.491706
iter 20 value 94.336015
iter 30 value 84.674667
iter 40 value 83.818580
iter 50 value 83.555577
iter 60 value 83.552430
iter 70 value 83.486998
iter 80 value 83.459691
iter 90 value 83.453946
iter 100 value 83.426006
final value 83.426006
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 123.393154
iter 10 value 94.459652
iter 20 value 94.263932
iter 30 value 94.141284
iter 40 value 93.846568
iter 50 value 86.282817
iter 60 value 83.865378
iter 70 value 83.810179
iter 80 value 83.809264
iter 90 value 83.808916
final value 83.807111
converged
Fitting Repeat 4
# weights: 507
initial value 94.544606
iter 10 value 94.363074
iter 20 value 94.355054
iter 30 value 93.026808
iter 40 value 92.223515
iter 50 value 92.164848
iter 60 value 92.161503
iter 70 value 92.157910
final value 92.157865
converged
Fitting Repeat 5
# weights: 507
initial value 119.974043
iter 10 value 94.362304
iter 20 value 94.342219
iter 30 value 90.288913
iter 40 value 89.992893
final value 89.991874
converged
Fitting Repeat 1
# weights: 103
initial value 99.573701
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 108.144549
iter 10 value 92.298055
iter 20 value 92.281097
final value 92.281082
converged
Fitting Repeat 3
# weights: 103
initial value 95.873722
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.930735
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 101.074937
iter 10 value 94.331648
final value 94.326054
converged
Fitting Repeat 1
# weights: 305
initial value 103.575398
iter 10 value 94.363251
iter 10 value 94.363251
iter 10 value 94.363251
final value 94.363251
converged
Fitting Repeat 2
# weights: 305
initial value 97.308353
iter 10 value 92.299520
iter 20 value 92.281100
final value 92.281082
converged
Fitting Repeat 3
# weights: 305
initial value 100.878554
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 99.914165
iter 10 value 92.286306
iter 20 value 92.281086
final value 92.281082
converged
Fitting Repeat 5
# weights: 305
initial value 112.904933
iter 10 value 92.196388
iter 20 value 92.167217
final value 92.167190
converged
Fitting Repeat 1
# weights: 507
initial value 108.102638
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 97.399214
iter 10 value 91.149410
iter 20 value 90.905902
iter 30 value 90.896011
final value 90.895991
converged
Fitting Repeat 3
# weights: 507
initial value 104.804045
final value 94.326054
converged
Fitting Repeat 4
# weights: 507
initial value 106.427928
iter 10 value 92.291471
iter 20 value 92.281091
final value 92.281082
converged
Fitting Repeat 5
# weights: 507
initial value 109.147454
iter 10 value 91.581747
iter 20 value 91.465271
iter 30 value 91.366902
iter 40 value 91.362936
iter 50 value 91.362849
final value 91.362816
converged
Fitting Repeat 1
# weights: 103
initial value 99.693328
iter 10 value 92.153609
iter 20 value 87.891945
iter 30 value 87.008441
iter 40 value 83.263832
iter 50 value 82.055484
iter 60 value 80.521809
final value 80.510533
converged
Fitting Repeat 2
# weights: 103
initial value 107.992766
iter 10 value 94.410394
iter 20 value 92.303958
iter 30 value 92.244696
iter 40 value 88.903615
iter 50 value 86.379625
iter 60 value 84.062200
iter 70 value 83.477240
iter 80 value 83.161273
final value 83.156215
converged
Fitting Repeat 3
# weights: 103
initial value 96.247668
iter 10 value 94.106651
iter 20 value 91.325447
iter 30 value 89.201995
iter 40 value 88.160434
iter 50 value 87.954773
iter 60 value 87.928107
iter 70 value 86.069830
iter 80 value 82.518246
iter 90 value 81.309618
iter 100 value 80.537795
final value 80.537795
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 108.211131
iter 10 value 93.131835
iter 20 value 88.261642
iter 30 value 86.075646
iter 40 value 83.753263
iter 50 value 83.056532
iter 60 value 82.688031
iter 70 value 82.645760
iter 80 value 80.872204
iter 90 value 80.358239
final value 80.354083
converged
Fitting Repeat 5
# weights: 103
initial value 98.495630
iter 10 value 94.590255
iter 20 value 92.279143
iter 30 value 91.725470
iter 40 value 87.918211
iter 50 value 86.803065
iter 60 value 86.520599
iter 70 value 84.698705
iter 80 value 82.457418
iter 90 value 81.009845
iter 100 value 80.631862
final value 80.631862
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 115.815313
iter 10 value 96.766439
iter 20 value 94.170508
iter 30 value 88.015675
iter 40 value 84.917139
iter 50 value 84.219275
iter 60 value 83.053113
iter 70 value 79.820198
iter 80 value 79.142228
iter 90 value 78.982852
iter 100 value 78.831661
final value 78.831661
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.712050
iter 10 value 94.785032
iter 20 value 91.948465
iter 30 value 84.519107
iter 40 value 82.661073
iter 50 value 81.577052
iter 60 value 81.074413
iter 70 value 80.196559
iter 80 value 80.154818
iter 90 value 80.049657
iter 100 value 79.793787
final value 79.793787
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.645965
iter 10 value 93.697435
iter 20 value 91.619822
iter 30 value 90.999356
iter 40 value 90.985351
iter 50 value 87.490320
iter 60 value 84.138538
iter 70 value 83.280627
iter 80 value 80.030217
iter 90 value 79.436072
iter 100 value 79.333719
final value 79.333719
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 109.845123
iter 10 value 91.239482
iter 20 value 83.707483
iter 30 value 83.005534
iter 40 value 81.763422
iter 50 value 79.859638
iter 60 value 79.328930
iter 70 value 79.153957
iter 80 value 78.949386
iter 90 value 78.917354
iter 100 value 78.915561
final value 78.915561
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.429721
iter 10 value 94.317944
iter 20 value 93.006025
iter 30 value 91.354096
iter 40 value 87.904184
iter 50 value 83.467034
iter 60 value 81.239399
iter 70 value 80.587346
iter 80 value 80.483866
iter 90 value 79.939532
iter 100 value 79.777463
final value 79.777463
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 147.693650
iter 10 value 95.594475
iter 20 value 88.444559
iter 30 value 85.849945
iter 40 value 83.550857
iter 50 value 81.849468
iter 60 value 80.253073
iter 70 value 79.584965
iter 80 value 79.440417
iter 90 value 79.349599
iter 100 value 79.247973
final value 79.247973
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.155806
iter 10 value 93.749688
iter 20 value 86.720151
iter 30 value 84.535057
iter 40 value 84.243353
iter 50 value 83.123297
iter 60 value 81.185567
iter 70 value 80.500228
iter 80 value 79.830656
iter 90 value 79.386121
iter 100 value 79.260383
final value 79.260383
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 120.221426
iter 10 value 94.311672
iter 20 value 85.154226
iter 30 value 83.571390
iter 40 value 82.181800
iter 50 value 82.021111
iter 60 value 81.865613
iter 70 value 80.795950
iter 80 value 80.193697
iter 90 value 79.992903
iter 100 value 79.913694
final value 79.913694
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 122.377994
iter 10 value 94.442814
iter 20 value 93.412411
iter 30 value 87.430684
iter 40 value 84.655495
iter 50 value 84.050085
iter 60 value 82.067300
iter 70 value 79.678317
iter 80 value 79.008799
iter 90 value 78.844601
iter 100 value 78.732879
final value 78.732879
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 130.546873
iter 10 value 94.985701
iter 20 value 92.306549
iter 30 value 89.955941
iter 40 value 84.927866
iter 50 value 82.431149
iter 60 value 82.014485
iter 70 value 81.824311
iter 80 value 81.561719
iter 90 value 80.685947
iter 100 value 79.518589
final value 79.518589
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.048411
final value 94.485775
converged
Fitting Repeat 2
# weights: 103
initial value 100.162409
iter 10 value 94.485749
iter 20 value 94.484235
final value 94.484224
converged
Fitting Repeat 3
# weights: 103
initial value 107.823224
final value 94.486105
converged
Fitting Repeat 4
# weights: 103
initial value 101.493675
final value 94.485840
converged
Fitting Repeat 5
# weights: 103
initial value 98.491013
iter 10 value 94.485806
iter 20 value 94.474937
iter 30 value 92.298550
iter 40 value 92.291339
iter 50 value 92.290789
iter 60 value 91.509671
final value 91.509559
converged
Fitting Repeat 1
# weights: 305
initial value 99.139099
iter 10 value 92.180440
iter 20 value 92.176921
iter 30 value 91.062287
iter 40 value 90.956902
iter 50 value 90.784801
iter 60 value 90.044850
iter 70 value 84.945658
iter 80 value 79.882931
iter 90 value 78.301417
iter 100 value 78.247852
final value 78.247852
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 98.852082
iter 10 value 93.536568
iter 20 value 93.305930
iter 30 value 93.301950
iter 40 value 93.250716
iter 50 value 91.536615
iter 60 value 91.506446
iter 70 value 91.506376
iter 80 value 90.026037
iter 90 value 83.529396
iter 100 value 78.849890
final value 78.849890
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.484732
iter 10 value 94.488571
iter 20 value 94.484232
final value 94.484219
converged
Fitting Repeat 4
# weights: 305
initial value 102.574772
iter 10 value 92.299262
iter 20 value 92.292399
iter 30 value 92.118506
iter 40 value 91.380513
iter 50 value 86.145643
iter 60 value 81.778232
iter 70 value 81.193428
iter 80 value 81.000602
iter 90 value 80.776364
iter 100 value 80.775874
final value 80.775874
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.983077
iter 10 value 84.239031
iter 20 value 81.720405
iter 30 value 81.635622
iter 40 value 81.634155
iter 50 value 81.628485
iter 60 value 81.540317
iter 70 value 81.437570
iter 80 value 81.379880
iter 90 value 81.074101
iter 100 value 81.073329
final value 81.073329
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 99.850360
iter 10 value 94.492459
iter 20 value 94.373671
iter 30 value 92.309300
iter 40 value 92.094362
iter 50 value 86.650561
iter 60 value 85.873981
iter 70 value 83.960242
iter 80 value 81.519817
iter 90 value 81.081243
iter 100 value 81.071965
final value 81.071965
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 100.577851
iter 10 value 92.260857
iter 20 value 92.244650
iter 30 value 90.652910
iter 40 value 83.992378
iter 50 value 83.759045
iter 60 value 83.728752
iter 70 value 83.727482
final value 83.726695
converged
Fitting Repeat 3
# weights: 507
initial value 101.405938
iter 10 value 92.190034
iter 20 value 92.179885
iter 30 value 92.172896
iter 40 value 92.172532
iter 40 value 92.172531
iter 40 value 92.172531
final value 92.172531
converged
Fitting Repeat 4
# weights: 507
initial value 98.266230
iter 10 value 94.490418
iter 20 value 93.517303
iter 30 value 83.340126
final value 83.338359
converged
Fitting Repeat 5
# weights: 507
initial value 109.966592
iter 10 value 92.298810
iter 20 value 92.293780
iter 30 value 91.973984
iter 40 value 87.012398
iter 50 value 81.215587
iter 60 value 80.554868
iter 70 value 80.111294
iter 80 value 79.281500
iter 90 value 79.054103
iter 100 value 78.995055
final value 78.995055
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 97.782928
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.824524
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 95.552171
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 111.934151
final value 93.671508
converged
Fitting Repeat 5
# weights: 103
initial value 102.877995
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 99.682757
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 95.603530
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 103.118927
iter 10 value 94.038252
iter 10 value 94.038251
iter 10 value 94.038251
final value 94.038251
converged
Fitting Repeat 4
# weights: 305
initial value 99.224835
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 102.897516
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 97.991371
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 141.610724
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 97.774743
iter 10 value 93.912813
final value 93.912644
converged
Fitting Repeat 4
# weights: 507
initial value 108.585831
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 96.491943
iter 10 value 94.064917
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 96.935402
iter 10 value 94.025943
iter 20 value 89.759463
iter 30 value 88.026087
iter 40 value 87.687471
iter 50 value 87.371318
iter 60 value 86.948418
iter 70 value 86.177733
final value 86.167487
converged
Fitting Repeat 2
# weights: 103
initial value 96.283103
iter 10 value 94.031497
iter 20 value 92.170465
iter 30 value 88.403916
iter 40 value 87.742006
iter 50 value 87.392302
iter 60 value 86.823715
iter 70 value 86.498641
iter 80 value 84.417442
iter 90 value 84.388268
iter 100 value 84.347627
final value 84.347627
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 98.606586
iter 10 value 94.054891
iter 20 value 94.009174
iter 30 value 90.573295
iter 40 value 90.186365
iter 50 value 87.494972
iter 60 value 85.418764
iter 70 value 84.393860
iter 80 value 84.255201
iter 90 value 84.251606
final value 84.251550
converged
Fitting Repeat 4
# weights: 103
initial value 105.733926
iter 10 value 94.040336
iter 20 value 90.328282
iter 30 value 86.796949
iter 40 value 86.047565
iter 50 value 85.995349
iter 60 value 85.979035
iter 70 value 85.854982
iter 80 value 85.302208
iter 90 value 85.145379
iter 100 value 85.054602
final value 85.054602
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 96.232195
iter 10 value 93.974080
iter 20 value 90.064565
iter 30 value 88.388623
iter 40 value 86.854032
iter 50 value 85.307464
iter 60 value 84.883300
iter 70 value 84.644061
final value 84.643620
converged
Fitting Repeat 1
# weights: 305
initial value 111.552453
iter 10 value 94.090179
iter 20 value 93.144238
iter 30 value 89.783527
iter 40 value 87.203351
iter 50 value 85.356619
iter 60 value 84.905705
iter 70 value 84.536337
iter 80 value 84.411508
iter 90 value 84.267976
iter 100 value 84.109435
final value 84.109435
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 109.501499
iter 10 value 93.953391
iter 20 value 86.110934
iter 30 value 85.977457
iter 40 value 85.934546
iter 50 value 85.714579
iter 60 value 84.805662
iter 70 value 84.257430
iter 80 value 83.923494
iter 90 value 83.896230
iter 100 value 83.852950
final value 83.852950
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 109.817845
iter 10 value 93.827819
iter 20 value 87.337809
iter 30 value 86.147562
iter 40 value 84.534906
iter 50 value 83.901453
iter 60 value 83.732108
iter 70 value 83.629488
iter 80 value 83.484569
iter 90 value 83.277341
iter 100 value 83.270636
final value 83.270636
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 110.725183
iter 10 value 95.236419
iter 20 value 94.562581
iter 30 value 93.639213
iter 40 value 87.331586
iter 50 value 86.872192
iter 60 value 84.979848
iter 70 value 81.967249
iter 80 value 81.479649
iter 90 value 81.220759
iter 100 value 81.084797
final value 81.084797
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.509990
iter 10 value 93.993976
iter 20 value 93.090022
iter 30 value 90.355943
iter 40 value 85.537221
iter 50 value 84.961833
iter 60 value 84.798928
iter 70 value 84.590826
iter 80 value 84.469501
iter 90 value 84.391843
iter 100 value 84.366601
final value 84.366601
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.726161
iter 10 value 87.378019
iter 20 value 84.506300
iter 30 value 83.584035
iter 40 value 83.125539
iter 50 value 82.922432
iter 60 value 82.562513
iter 70 value 82.133903
iter 80 value 81.809022
iter 90 value 81.567686
iter 100 value 81.438774
final value 81.438774
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.424972
iter 10 value 94.082815
iter 20 value 89.327027
iter 30 value 86.338590
iter 40 value 84.899576
iter 50 value 83.184856
iter 60 value 82.412109
iter 70 value 82.331759
iter 80 value 81.591301
iter 90 value 81.392854
iter 100 value 81.254491
final value 81.254491
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 106.109766
iter 10 value 94.007136
iter 20 value 93.742289
iter 30 value 92.564615
iter 40 value 92.268146
iter 50 value 91.785986
iter 60 value 86.766419
iter 70 value 84.896576
iter 80 value 83.345072
iter 90 value 82.173145
iter 100 value 81.532456
final value 81.532456
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.847023
iter 10 value 93.962548
iter 20 value 87.827451
iter 30 value 85.601534
iter 40 value 85.126866
iter 50 value 84.426334
iter 60 value 83.755651
iter 70 value 82.999736
iter 80 value 82.091267
iter 90 value 81.450381
iter 100 value 81.367081
final value 81.367081
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 127.612998
iter 10 value 94.078773
iter 20 value 87.166661
iter 30 value 85.461792
iter 40 value 84.436878
iter 50 value 83.991982
iter 60 value 83.778329
iter 70 value 83.701529
iter 80 value 83.669019
iter 90 value 83.654095
iter 100 value 83.639948
final value 83.639948
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.706979
final value 94.054508
converged
Fitting Repeat 2
# weights: 103
initial value 96.105610
iter 10 value 94.016809
iter 20 value 94.015532
iter 30 value 93.962322
final value 93.912715
converged
Fitting Repeat 3
# weights: 103
initial value 105.688246
final value 94.054423
converged
Fitting Repeat 4
# weights: 103
initial value 100.979301
iter 10 value 93.983935
iter 20 value 93.464631
iter 30 value 93.009303
iter 40 value 93.002390
iter 50 value 92.983525
iter 60 value 92.982152
final value 92.982149
converged
Fitting Repeat 5
# weights: 103
initial value 101.840876
final value 94.054572
converged
Fitting Repeat 1
# weights: 305
initial value 96.143629
iter 10 value 94.057312
iter 20 value 93.958164
iter 30 value 85.508208
iter 40 value 84.530952
final value 84.518815
converged
Fitting Repeat 2
# weights: 305
initial value 98.214151
iter 10 value 94.043528
iter 20 value 93.072887
iter 30 value 85.630762
iter 40 value 85.131361
iter 50 value 85.130430
final value 85.130427
converged
Fitting Repeat 3
# weights: 305
initial value 100.503583
iter 10 value 93.772744
iter 20 value 93.676142
iter 30 value 93.669766
iter 40 value 87.003011
iter 50 value 87.000314
iter 60 value 86.461352
iter 70 value 85.859372
iter 80 value 85.305569
iter 90 value 84.824279
iter 100 value 84.821589
final value 84.821589
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 113.970126
iter 10 value 94.059021
iter 20 value 94.053892
iter 30 value 93.922365
iter 40 value 93.913886
iter 50 value 93.913734
iter 60 value 93.913547
iter 70 value 93.912962
iter 80 value 93.912829
final value 93.912783
converged
Fitting Repeat 5
# weights: 305
initial value 110.458378
iter 10 value 94.057433
iter 20 value 94.052804
iter 30 value 93.225137
iter 40 value 93.108143
iter 50 value 92.936218
iter 60 value 92.935651
final value 92.935488
converged
Fitting Repeat 1
# weights: 507
initial value 126.850433
iter 10 value 94.066815
iter 20 value 94.034104
iter 30 value 86.273398
iter 40 value 86.270032
iter 50 value 86.133514
iter 60 value 86.089936
iter 70 value 86.071569
iter 80 value 85.862835
iter 90 value 85.659002
iter 100 value 85.611544
final value 85.611544
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 94.624922
iter 10 value 93.810956
iter 20 value 92.709981
final value 92.709961
converged
Fitting Repeat 3
# weights: 507
initial value 121.388892
iter 10 value 88.361549
iter 20 value 87.797644
iter 30 value 87.776016
iter 40 value 87.775573
iter 50 value 87.770189
final value 87.769413
converged
Fitting Repeat 4
# weights: 507
initial value 99.071331
iter 10 value 90.340356
iter 20 value 87.892146
iter 30 value 87.129469
final value 87.127881
converged
Fitting Repeat 5
# weights: 507
initial value 101.310181
iter 10 value 94.060802
iter 20 value 94.025605
iter 30 value 89.570282
iter 40 value 87.936433
iter 50 value 87.427335
iter 60 value 83.090075
iter 70 value 82.714952
iter 80 value 82.707642
final value 82.706736
converged
Fitting Repeat 1
# weights: 103
initial value 98.516352
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.877205
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 97.549483
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 113.183274
final value 94.038251
converged
Fitting Repeat 5
# weights: 103
initial value 94.842904
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 112.217109
final value 94.042012
converged
Fitting Repeat 2
# weights: 305
initial value 99.834006
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 95.765266
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 106.656899
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 112.692205
final value 94.038251
converged
Fitting Repeat 1
# weights: 507
initial value 94.081132
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 110.392825
iter 10 value 92.416197
iter 20 value 83.019294
iter 30 value 82.931378
final value 82.931272
converged
Fitting Repeat 3
# weights: 507
initial value 98.793643
iter 10 value 94.038252
iter 10 value 94.038251
iter 10 value 94.038251
final value 94.038251
converged
Fitting Repeat 4
# weights: 507
initial value 104.770694
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 105.950641
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 100.286724
iter 10 value 94.067077
iter 20 value 93.974264
iter 30 value 91.795221
iter 40 value 91.522808
iter 50 value 91.456270
final value 91.453025
converged
Fitting Repeat 2
# weights: 103
initial value 101.808884
iter 10 value 93.994546
iter 20 value 89.693451
iter 30 value 88.646380
iter 40 value 86.940381
iter 50 value 85.042479
iter 60 value 83.403381
iter 70 value 81.819873
iter 80 value 81.222360
iter 90 value 81.184850
final value 81.184321
converged
Fitting Repeat 3
# weights: 103
initial value 97.043682
iter 10 value 93.986906
iter 20 value 85.137716
iter 30 value 84.638322
iter 40 value 83.598806
iter 50 value 83.517334
final value 83.515784
converged
Fitting Repeat 4
# weights: 103
initial value 99.180097
iter 10 value 94.057256
iter 20 value 93.859518
iter 30 value 89.925410
iter 40 value 87.234127
iter 50 value 85.491708
iter 60 value 82.935639
iter 70 value 82.298525
iter 80 value 81.653951
iter 90 value 81.574101
iter 100 value 81.536374
final value 81.536374
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 117.772869
iter 10 value 94.066852
iter 20 value 94.057926
iter 30 value 94.016069
iter 40 value 90.858600
iter 50 value 88.980363
iter 60 value 84.418198
iter 70 value 83.759312
iter 80 value 83.708785
final value 83.707589
converged
Fitting Repeat 1
# weights: 305
initial value 99.926255
iter 10 value 94.266167
iter 20 value 94.080110
iter 30 value 85.483048
iter 40 value 83.438149
iter 50 value 82.828277
iter 60 value 82.462375
iter 70 value 82.132848
iter 80 value 82.058271
iter 90 value 81.738828
iter 100 value 81.502091
final value 81.502091
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 108.508163
iter 10 value 95.631285
iter 20 value 87.551107
iter 30 value 85.591717
iter 40 value 84.414491
iter 50 value 83.147229
iter 60 value 81.992208
iter 70 value 81.496532
iter 80 value 81.470690
iter 90 value 81.242218
iter 100 value 80.918238
final value 80.918238
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 110.504628
iter 10 value 94.043157
iter 20 value 91.936613
iter 30 value 86.225393
iter 40 value 84.171072
iter 50 value 83.500343
iter 60 value 83.404370
iter 70 value 83.066914
iter 80 value 82.661422
iter 90 value 81.970142
iter 100 value 80.875968
final value 80.875968
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.463481
iter 10 value 93.944236
iter 20 value 92.303641
iter 30 value 88.645114
iter 40 value 84.249527
iter 50 value 83.416680
iter 60 value 81.883538
iter 70 value 80.900892
iter 80 value 80.538532
iter 90 value 80.463152
iter 100 value 80.332083
final value 80.332083
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 107.611003
iter 10 value 93.914161
iter 20 value 85.212555
iter 30 value 83.543712
iter 40 value 82.438102
iter 50 value 80.661440
iter 60 value 80.302990
iter 70 value 80.212949
iter 80 value 80.103292
iter 90 value 80.057040
iter 100 value 80.024921
final value 80.024921
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.783449
iter 10 value 93.999473
iter 20 value 89.245352
iter 30 value 84.612192
iter 40 value 84.060384
iter 50 value 83.408403
iter 60 value 82.944279
iter 70 value 82.886402
iter 80 value 82.873156
iter 90 value 82.869219
iter 100 value 82.696126
final value 82.696126
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 110.899391
iter 10 value 96.729177
iter 20 value 92.591654
iter 30 value 86.538096
iter 40 value 84.099317
iter 50 value 82.619804
iter 60 value 82.294114
iter 70 value 82.132169
iter 80 value 82.044037
iter 90 value 81.815038
iter 100 value 81.204118
final value 81.204118
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.172128
iter 10 value 93.682701
iter 20 value 87.619188
iter 30 value 84.962069
iter 40 value 83.765741
iter 50 value 82.279256
iter 60 value 81.741105
iter 70 value 80.515295
iter 80 value 79.682686
iter 90 value 79.499004
iter 100 value 79.406128
final value 79.406128
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.884097
iter 10 value 95.869339
iter 20 value 84.751807
iter 30 value 83.784329
iter 40 value 82.414176
iter 50 value 82.336822
iter 60 value 81.219341
iter 70 value 80.431993
iter 80 value 80.158319
iter 90 value 79.782473
iter 100 value 79.644710
final value 79.644710
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.578810
iter 10 value 94.909000
iter 20 value 83.971447
iter 30 value 81.921586
iter 40 value 80.894754
iter 50 value 80.646317
iter 60 value 80.519204
iter 70 value 79.904161
iter 80 value 79.669790
iter 90 value 79.609876
iter 100 value 79.596517
final value 79.596517
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.220174
final value 94.054681
converged
Fitting Repeat 2
# weights: 103
initial value 97.687072
final value 94.054526
converged
Fitting Repeat 3
# weights: 103
initial value 102.407354
iter 10 value 94.054575
iter 20 value 94.052959
iter 30 value 83.522696
iter 40 value 82.283809
iter 50 value 82.035909
iter 60 value 82.033164
final value 82.018634
converged
Fitting Repeat 4
# weights: 103
initial value 99.150844
iter 10 value 94.054733
final value 94.053004
converged
Fitting Repeat 5
# weights: 103
initial value 107.914205
final value 94.039930
converged
Fitting Repeat 1
# weights: 305
initial value 104.462088
iter 10 value 94.058588
iter 20 value 94.048253
iter 30 value 83.060444
iter 40 value 82.879405
iter 50 value 82.857516
iter 60 value 82.814620
iter 70 value 82.786358
iter 80 value 82.779077
iter 90 value 82.775142
iter 100 value 82.764955
final value 82.764955
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 109.885275
iter 10 value 94.057650
iter 20 value 94.019563
iter 30 value 89.335986
iter 40 value 89.270378
iter 50 value 87.322459
iter 60 value 87.321660
iter 70 value 87.318980
iter 80 value 87.309820
iter 90 value 87.308241
final value 87.307768
converged
Fitting Repeat 3
# weights: 305
initial value 94.491793
iter 10 value 94.058140
iter 20 value 93.302134
iter 30 value 83.062961
iter 40 value 82.935505
iter 50 value 82.897455
iter 60 value 82.882827
iter 70 value 82.876730
iter 80 value 82.609298
iter 90 value 82.413970
iter 100 value 82.413725
final value 82.413725
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 96.674819
iter 10 value 94.057787
iter 20 value 94.052813
iter 30 value 83.268489
iter 40 value 83.050980
iter 50 value 83.009057
iter 60 value 82.705883
iter 70 value 81.645168
iter 80 value 80.360658
iter 90 value 79.608450
iter 100 value 79.188821
final value 79.188821
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 94.738320
iter 10 value 94.057636
iter 20 value 91.941959
iter 30 value 83.962848
iter 40 value 82.898464
iter 50 value 82.250905
iter 60 value 82.209589
iter 70 value 82.044229
iter 80 value 81.411905
iter 90 value 81.151907
iter 100 value 81.144600
final value 81.144600
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 99.488926
iter 10 value 92.497110
iter 20 value 81.614291
iter 30 value 80.242250
iter 40 value 80.241062
iter 50 value 80.237352
iter 60 value 80.232195
iter 70 value 79.902625
iter 80 value 79.151152
iter 90 value 78.833569
iter 100 value 78.788955
final value 78.788955
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 119.473671
iter 10 value 94.047077
iter 20 value 93.232638
iter 30 value 90.986138
iter 40 value 82.845631
iter 50 value 82.745295
iter 60 value 82.529688
iter 70 value 82.200280
iter 80 value 82.200097
final value 82.200053
converged
Fitting Repeat 3
# weights: 507
initial value 97.785796
iter 10 value 94.061346
iter 20 value 93.277582
iter 30 value 83.063055
iter 40 value 83.033660
iter 50 value 82.996048
iter 60 value 82.984247
iter 70 value 82.973760
iter 80 value 82.639092
iter 90 value 82.488186
iter 100 value 82.481152
final value 82.481152
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 101.650912
iter 10 value 94.060922
iter 20 value 92.951388
iter 30 value 82.990303
final value 82.982792
converged
Fitting Repeat 5
# weights: 507
initial value 96.234375
iter 10 value 91.322790
iter 20 value 91.305263
iter 30 value 81.915837
iter 40 value 81.850641
iter 50 value 81.584685
iter 60 value 81.570004
iter 70 value 80.700764
iter 80 value 80.175290
iter 90 value 79.960962
iter 100 value 79.958174
final value 79.958174
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 127.415510
iter 10 value 117.861302
iter 20 value 114.987383
iter 30 value 114.731116
iter 40 value 114.728725
iter 50 value 114.726941
iter 60 value 114.638770
iter 70 value 114.634736
final value 114.634731
converged
Fitting Repeat 2
# weights: 305
initial value 130.537786
iter 10 value 117.894957
iter 20 value 108.523121
iter 30 value 107.259232
iter 40 value 107.253760
iter 50 value 107.253519
iter 60 value 106.981301
iter 70 value 106.806207
final value 106.806180
converged
Fitting Repeat 3
# weights: 305
initial value 125.174970
iter 10 value 117.763486
iter 20 value 117.391701
iter 30 value 112.492546
iter 40 value 110.311816
iter 50 value 107.642893
iter 60 value 100.312638
iter 70 value 99.416252
iter 80 value 99.131123
iter 90 value 99.014646
iter 100 value 99.003805
final value 99.003805
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 142.359232
iter 10 value 117.893230
iter 20 value 117.483959
iter 30 value 106.921749
iter 40 value 106.795325
iter 50 value 106.724660
iter 60 value 106.682111
iter 70 value 106.671444
iter 80 value 104.301063
iter 90 value 103.843841
iter 100 value 103.717665
final value 103.717665
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 126.977224
iter 10 value 117.895689
iter 20 value 117.889922
iter 30 value 117.164291
iter 40 value 109.175172
iter 50 value 108.429523
iter 60 value 108.425416
iter 70 value 107.278174
iter 80 value 107.259377
iter 90 value 107.116199
iter 100 value 106.833802
final value 106.833802
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 -- Thu Mar 28 01:51:36 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 2.07 49.23
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 31.78 | 1.20 | 33.07 | |
| FreqInteractors | 0.25 | 0.05 | 0.30 | |
| calculateAAC | 0.03 | 0.01 | 0.05 | |
| calculateAutocor | 0.35 | 0.07 | 0.41 | |
| calculateCTDC | 0.07 | 0.00 | 0.08 | |
| calculateCTDD | 0.61 | 0.07 | 0.68 | |
| calculateCTDT | 0.29 | 0.00 | 0.28 | |
| calculateCTriad | 0.37 | 0.02 | 0.40 | |
| calculateDC | 0.08 | 0.03 | 0.10 | |
| calculateF | 0.37 | 0.02 | 0.40 | |
| calculateKSAAP | 0.11 | 0.00 | 0.10 | |
| calculateQD_Sm | 1.99 | 0.11 | 2.10 | |
| calculateTC | 2.28 | 0.12 | 2.41 | |
| calculateTC_Sm | 0.30 | 0.03 | 0.33 | |
| corr_plot | 31.30 | 0.97 | 32.28 | |
| enrichfindP | 0.58 | 0.05 | 14.31 | |
| enrichfind_hp | 0.09 | 0.01 | 1.02 | |
| enrichplot | 0.48 | 0.00 | 0.48 | |
| filter_missing_values | 0.02 | 0.00 | 0.02 | |
| getFASTA | 0.03 | 0.04 | 2.42 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.11 | 0.00 | 0.11 | |
| pred_ensembel | 13.30 | 0.59 | 10.23 | |
| var_imp | 32.59 | 1.14 | 33.75 | |