| Back to Multiple platform build/check report for BioC 3.18: simplified long |
|
This page was generated on 2024-04-17 11:36:02 -0400 (Wed, 17 Apr 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" | 4676 |
| palomino4 | Windows Server 2022 Datacenter | x64 | 4.3.3 (2024-02-29 ucrt) -- "Angel Food Cake" | 4414 |
| merida1 | macOS 12.7.1 Monterey | x86_64 | 4.3.3 (2024-02-29) -- "Angel Food Cake" | 4437 |
| 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: /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings HPiP_1.8.0.tar.gz |
| StartedAt: 2024-04-15 23:50:41 -0400 (Mon, 15 Apr 2024) |
| EndedAt: 2024-04-16 00:13:15 -0400 (Tue, 16 Apr 2024) |
| EllapsedTime: 1354.8 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.18-bioc/R/site-library --timings HPiP_1.8.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck’
* using R version 4.3.3 (2024-02-29)
* using platform: x86_64-pc-linux-gnu (64-bit)
* R was compiled by
gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
GNU Fortran (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
* running under: Ubuntu 22.04.4 LTS
* using session charset: UTF-8
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.8.0’
* 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 for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... 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 loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... 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 35.452 0.972 36.425
FSmethod 34.518 0.776 35.296
corr_plot 34.397 0.488 34.885
pred_ensembel 13.456 0.560 10.701
enrichfindP 0.469 0.048 9.622
* 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 ...
‘HPiP_tutorial.Rmd’ using ‘UTF-8’... OK
OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 1 NOTE
See
‘/home/biocbuild/bbs-3.18-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.18-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.18-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** using staged installation ** R ** data ** inst ** byte-compile and prepare package for lazy loading ** help *** installing help indices ** building package indices ** installing vignettes ** testing if installed package can be loaded from temporary location ** testing if installed package can be loaded from final location ** testing if installed package keeps a record of temporary installation path * DONE (HPiP)
HPiP.Rcheck/tests/runTests.Rout
R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (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 94.750978
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 94.571468
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 109.811643
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.194553
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 105.869559
iter 10 value 94.275362
iter 10 value 94.275362
iter 10 value 94.275362
final value 94.275362
converged
Fitting Repeat 1
# weights: 305
initial value 101.637063
iter 10 value 93.893341
final value 93.831039
converged
Fitting Repeat 2
# weights: 305
initial value 109.894267
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 101.397370
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 95.875994
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 99.502235
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 115.663018
iter 10 value 94.305896
final value 94.305882
converged
Fitting Repeat 2
# weights: 507
initial value 104.295666
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 103.982660
final value 94.275362
converged
Fitting Repeat 4
# weights: 507
initial value 100.704547
final value 94.448052
converged
Fitting Repeat 5
# weights: 507
initial value 100.892852
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 97.954327
iter 10 value 94.488560
iter 20 value 94.345266
iter 30 value 86.092464
iter 40 value 84.106750
iter 50 value 83.715153
iter 60 value 83.473569
iter 70 value 81.917909
iter 80 value 81.882583
final value 81.882582
converged
Fitting Repeat 2
# weights: 103
initial value 98.054408
iter 10 value 94.489904
iter 20 value 94.482368
iter 30 value 94.360332
iter 40 value 94.352643
iter 50 value 94.346553
iter 60 value 94.336115
iter 70 value 94.155556
iter 80 value 92.839728
iter 90 value 86.604517
iter 100 value 84.288128
final value 84.288128
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.170908
iter 10 value 94.459238
iter 20 value 86.199875
iter 30 value 84.884070
iter 40 value 84.372083
iter 50 value 83.036558
iter 60 value 82.095049
iter 70 value 81.882586
final value 81.882582
converged
Fitting Repeat 4
# weights: 103
initial value 104.436199
iter 10 value 94.476891
iter 20 value 87.069253
iter 30 value 84.784946
iter 40 value 84.473950
iter 50 value 83.493388
iter 60 value 82.720309
iter 70 value 82.290132
iter 80 value 81.594729
iter 90 value 81.547469
final value 81.547435
converged
Fitting Repeat 5
# weights: 103
initial value 98.970151
iter 10 value 94.488533
iter 20 value 94.314645
iter 30 value 86.194157
iter 40 value 85.504215
iter 50 value 85.124367
iter 60 value 84.529050
iter 70 value 83.315879
iter 80 value 83.165303
iter 90 value 83.143753
iter 100 value 82.766719
final value 82.766719
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 103.838401
iter 10 value 94.295377
iter 20 value 85.340731
iter 30 value 83.904193
iter 40 value 83.759902
iter 50 value 83.257562
iter 60 value 83.032866
iter 70 value 82.495367
iter 80 value 81.073836
iter 90 value 80.710015
iter 100 value 80.674780
final value 80.674780
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.936861
iter 10 value 94.497395
iter 20 value 86.371563
iter 30 value 84.578146
iter 40 value 82.674579
iter 50 value 81.576086
iter 60 value 81.140281
iter 70 value 80.999429
iter 80 value 80.761597
iter 90 value 80.520265
iter 100 value 80.482811
final value 80.482811
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.756115
iter 10 value 94.417146
iter 20 value 86.051468
iter 30 value 84.701484
iter 40 value 83.206065
iter 50 value 82.928193
iter 60 value 82.792036
iter 70 value 82.668237
iter 80 value 81.666678
iter 90 value 80.468794
iter 100 value 80.378192
final value 80.378192
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.390532
iter 10 value 94.484748
iter 20 value 93.835547
iter 30 value 92.571609
iter 40 value 89.196967
iter 50 value 86.861319
iter 60 value 85.670990
iter 70 value 85.340163
iter 80 value 84.254361
iter 90 value 82.395794
iter 100 value 81.147243
final value 81.147243
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.565298
iter 10 value 94.585444
iter 20 value 93.659063
iter 30 value 88.008582
iter 40 value 86.011885
iter 50 value 83.254814
iter 60 value 82.486174
iter 70 value 81.812895
iter 80 value 81.718928
iter 90 value 81.243052
iter 100 value 80.966001
final value 80.966001
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 130.633032
iter 10 value 93.917389
iter 20 value 84.702326
iter 30 value 83.756960
iter 40 value 82.881162
iter 50 value 81.888806
iter 60 value 81.637968
iter 70 value 80.955867
iter 80 value 80.838787
iter 90 value 80.644161
iter 100 value 80.490362
final value 80.490362
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 124.893000
iter 10 value 94.547255
iter 20 value 93.984274
iter 30 value 87.848977
iter 40 value 84.930089
iter 50 value 83.235757
iter 60 value 82.164039
iter 70 value 80.779960
iter 80 value 80.699341
iter 90 value 80.396320
iter 100 value 80.216033
final value 80.216033
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 119.591239
iter 10 value 100.618764
iter 20 value 94.236447
iter 30 value 90.510799
iter 40 value 86.848704
iter 50 value 84.379170
iter 60 value 83.311219
iter 70 value 81.867820
iter 80 value 80.663086
iter 90 value 80.160169
iter 100 value 79.950344
final value 79.950344
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.369352
iter 10 value 90.855763
iter 20 value 86.067997
iter 30 value 83.976483
iter 40 value 83.187115
iter 50 value 81.777684
iter 60 value 81.431040
iter 70 value 80.914813
iter 80 value 80.631590
iter 90 value 80.474925
iter 100 value 80.386203
final value 80.386203
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.992534
iter 10 value 94.483784
iter 20 value 85.293731
iter 30 value 84.323578
iter 40 value 83.732696
iter 50 value 81.946173
iter 60 value 81.077602
iter 70 value 80.630585
iter 80 value 80.272158
iter 90 value 80.114004
iter 100 value 79.962085
final value 79.962085
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 110.940291
final value 94.485763
converged
Fitting Repeat 2
# weights: 103
initial value 96.633088
iter 10 value 94.486101
iter 20 value 93.395892
iter 30 value 84.195473
iter 30 value 84.195472
iter 40 value 84.054066
iter 50 value 84.051590
iter 60 value 83.960649
iter 60 value 83.960649
iter 60 value 83.960649
final value 83.960649
converged
Fitting Repeat 3
# weights: 103
initial value 96.954048
final value 94.485806
converged
Fitting Repeat 4
# weights: 103
initial value 105.377107
final value 94.486407
converged
Fitting Repeat 5
# weights: 103
initial value 98.552816
final value 94.277087
converged
Fitting Repeat 1
# weights: 305
initial value 102.454206
iter 10 value 94.489087
iter 20 value 93.723687
iter 30 value 92.625284
iter 40 value 89.813018
iter 50 value 89.809782
iter 60 value 84.221563
final value 84.193713
converged
Fitting Repeat 2
# weights: 305
initial value 97.673838
iter 10 value 94.489074
iter 20 value 94.473528
iter 30 value 94.128825
iter 40 value 90.827820
final value 90.818890
converged
Fitting Repeat 3
# weights: 305
initial value 96.422296
iter 10 value 92.492807
iter 20 value 87.933307
iter 30 value 87.136797
iter 40 value 87.125358
iter 50 value 86.410056
iter 60 value 86.405018
iter 70 value 86.398285
iter 80 value 86.394889
iter 90 value 86.394623
final value 86.394126
converged
Fitting Repeat 4
# weights: 305
initial value 123.127689
iter 10 value 94.489088
iter 20 value 94.376633
iter 30 value 89.197310
iter 40 value 88.430655
iter 50 value 88.425224
iter 60 value 88.314798
iter 70 value 86.178455
iter 80 value 85.330480
iter 90 value 84.389545
iter 100 value 84.387390
final value 84.387390
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 99.492204
iter 10 value 94.488883
iter 20 value 94.473194
iter 30 value 94.341189
iter 40 value 90.082863
iter 50 value 87.956097
iter 60 value 86.273941
iter 70 value 85.109366
iter 80 value 82.413859
iter 90 value 80.670478
iter 100 value 80.486189
final value 80.486189
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.600419
iter 10 value 94.494229
iter 20 value 94.489080
iter 30 value 92.018299
iter 40 value 91.566421
iter 50 value 91.465914
final value 91.465780
converged
Fitting Repeat 2
# weights: 507
initial value 110.170356
iter 10 value 94.321798
iter 20 value 92.360102
iter 30 value 87.952800
final value 87.952762
converged
Fitting Repeat 3
# weights: 507
initial value 124.120462
iter 10 value 94.494081
iter 20 value 94.119441
iter 30 value 91.749900
iter 40 value 86.132735
iter 50 value 86.041487
iter 60 value 85.775048
iter 70 value 85.755042
iter 80 value 85.398861
iter 90 value 84.510328
iter 100 value 84.491097
final value 84.491097
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 130.231369
iter 10 value 94.314165
iter 20 value 94.278857
iter 30 value 94.198188
iter 40 value 90.059190
iter 50 value 84.836783
iter 60 value 84.227440
iter 70 value 84.210261
iter 80 value 84.209621
final value 84.209243
converged
Fitting Repeat 5
# weights: 507
initial value 95.077309
iter 10 value 90.798572
iter 20 value 87.218360
iter 30 value 86.743603
iter 40 value 85.459043
iter 50 value 85.368289
final value 85.367200
converged
Fitting Repeat 1
# weights: 103
initial value 94.374125
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 95.589252
iter 10 value 86.392952
iter 20 value 85.478130
final value 85.101326
converged
Fitting Repeat 3
# weights: 103
initial value 94.512357
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 96.162946
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.772770
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 106.392494
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 96.776733
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 94.403633
iter 10 value 92.891056
iter 20 value 89.866315
iter 30 value 89.584012
iter 40 value 89.581403
final value 89.581291
converged
Fitting Repeat 4
# weights: 305
initial value 109.453463
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 97.332836
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 97.862155
iter 10 value 93.747273
iter 20 value 93.691390
final value 93.691359
converged
Fitting Repeat 2
# weights: 507
initial value 104.975739
final value 94.038251
converged
Fitting Repeat 3
# weights: 507
initial value 106.941349
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 95.519214
iter 10 value 93.692087
final value 93.679487
converged
Fitting Repeat 5
# weights: 507
initial value 105.135031
final value 94.052909
converged
Fitting Repeat 1
# weights: 103
initial value 103.652848
iter 10 value 94.002671
iter 20 value 87.410703
iter 30 value 87.217226
iter 40 value 86.595209
iter 50 value 85.771289
iter 60 value 85.228633
iter 70 value 85.124313
iter 80 value 85.045135
final value 85.044589
converged
Fitting Repeat 2
# weights: 103
initial value 99.874652
iter 10 value 94.030715
iter 20 value 89.888063
iter 30 value 88.574820
iter 40 value 86.993531
iter 50 value 85.132422
iter 60 value 84.257205
iter 70 value 84.120177
iter 80 value 84.101630
iter 90 value 83.715832
iter 100 value 83.419800
final value 83.419800
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 101.050195
iter 10 value 94.032196
iter 20 value 92.018866
iter 30 value 86.709163
iter 40 value 85.563059
iter 50 value 84.934884
iter 60 value 84.748175
final value 84.737736
converged
Fitting Repeat 4
# weights: 103
initial value 104.909134
iter 10 value 94.059533
iter 20 value 89.097677
iter 30 value 86.714386
iter 40 value 86.234202
iter 50 value 86.120835
iter 60 value 85.901158
iter 70 value 85.806541
iter 80 value 85.790802
iter 80 value 85.790801
iter 80 value 85.790801
final value 85.790801
converged
Fitting Repeat 5
# weights: 103
initial value 99.382485
iter 10 value 94.057927
iter 20 value 93.948645
iter 30 value 93.823814
iter 40 value 93.722380
iter 50 value 88.621955
iter 60 value 86.506562
iter 70 value 85.278823
iter 80 value 84.826527
iter 90 value 84.564777
iter 100 value 83.570038
final value 83.570038
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 105.770297
iter 10 value 94.028872
iter 20 value 88.572906
iter 30 value 86.647756
iter 40 value 86.455593
iter 50 value 85.410272
iter 60 value 84.747054
iter 70 value 83.307083
iter 80 value 82.093993
iter 90 value 81.709604
iter 100 value 81.161061
final value 81.161061
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 103.071756
iter 10 value 94.217161
iter 20 value 93.043552
iter 30 value 87.494770
iter 40 value 84.073460
iter 50 value 82.293565
iter 60 value 81.913312
iter 70 value 81.755515
iter 80 value 81.620482
iter 90 value 81.573398
iter 100 value 81.560694
final value 81.560694
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 108.414560
iter 10 value 94.084683
iter 20 value 92.987030
iter 30 value 88.094152
iter 40 value 87.175692
iter 50 value 86.244029
iter 60 value 86.033267
iter 70 value 84.903210
iter 80 value 84.209693
iter 90 value 83.070624
iter 100 value 82.237247
final value 82.237247
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 100.773563
iter 10 value 94.035151
iter 20 value 92.386399
iter 30 value 87.225001
iter 40 value 86.823864
iter 50 value 85.780836
iter 60 value 82.871866
iter 70 value 82.481202
iter 80 value 82.241574
iter 90 value 81.794771
iter 100 value 81.256484
final value 81.256484
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.456599
iter 10 value 93.994564
iter 20 value 88.008275
iter 30 value 87.177603
iter 40 value 86.448327
iter 50 value 86.176209
iter 60 value 85.825300
iter 70 value 85.626021
iter 80 value 85.285363
iter 90 value 84.324778
iter 100 value 82.767466
final value 82.767466
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 102.912770
iter 10 value 94.003879
iter 20 value 92.504186
iter 30 value 89.004730
iter 40 value 86.312410
iter 50 value 85.361847
iter 60 value 84.631213
iter 70 value 83.397192
iter 80 value 82.861087
iter 90 value 82.729343
iter 100 value 82.128432
final value 82.128432
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 112.904050
iter 10 value 94.068190
iter 20 value 91.700073
iter 30 value 85.094933
iter 40 value 83.653229
iter 50 value 82.995458
iter 60 value 82.183193
iter 70 value 82.035108
iter 80 value 81.948518
iter 90 value 81.706640
iter 100 value 81.597994
final value 81.597994
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 121.334799
iter 10 value 94.009321
iter 20 value 91.513677
iter 30 value 90.072464
iter 40 value 86.806289
iter 50 value 86.738116
iter 60 value 86.047296
iter 70 value 85.635537
iter 80 value 84.597940
iter 90 value 83.878020
iter 100 value 83.498410
final value 83.498410
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.797457
iter 10 value 94.247333
iter 20 value 89.782725
iter 30 value 87.673741
iter 40 value 86.854094
iter 50 value 85.230046
iter 60 value 84.050834
iter 70 value 82.828933
iter 80 value 81.734456
iter 90 value 81.434343
iter 100 value 81.131925
final value 81.131925
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 105.800863
iter 10 value 94.074373
iter 20 value 89.827068
iter 30 value 87.590394
iter 40 value 86.743272
iter 50 value 85.754682
iter 60 value 84.660438
iter 70 value 83.603236
iter 80 value 82.920065
iter 90 value 82.535332
iter 100 value 81.565913
final value 81.565913
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.329285
iter 10 value 94.054562
iter 20 value 94.052966
iter 30 value 92.518121
iter 40 value 88.998306
iter 50 value 88.910880
iter 60 value 88.908390
iter 70 value 88.904873
iter 80 value 85.070958
iter 90 value 84.936570
iter 100 value 84.930208
final value 84.930208
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 95.800545
final value 94.054395
converged
Fitting Repeat 3
# weights: 103
initial value 95.693690
final value 94.039988
converged
Fitting Repeat 4
# weights: 103
initial value 97.401742
final value 94.054488
converged
Fitting Repeat 5
# weights: 103
initial value 95.294972
iter 10 value 94.054664
iter 20 value 94.048905
iter 30 value 88.549920
iter 40 value 88.517637
iter 50 value 88.485411
final value 88.485249
converged
Fitting Repeat 1
# weights: 305
initial value 94.937560
iter 10 value 94.043499
iter 20 value 94.038402
iter 30 value 93.824816
iter 40 value 88.540655
iter 50 value 88.422719
iter 60 value 88.374420
iter 70 value 87.594825
final value 87.594779
converged
Fitting Repeat 2
# weights: 305
initial value 94.271028
iter 10 value 93.702599
iter 20 value 92.563624
iter 30 value 92.526822
iter 40 value 92.116417
iter 50 value 92.100207
iter 60 value 91.881114
iter 70 value 91.860692
final value 91.854974
converged
Fitting Repeat 3
# weights: 305
initial value 101.890765
iter 10 value 93.966799
iter 20 value 93.916308
iter 30 value 93.911935
final value 93.911919
converged
Fitting Repeat 4
# weights: 305
initial value 99.281386
iter 10 value 94.057811
iter 20 value 91.552720
iter 30 value 86.379634
iter 40 value 85.664348
iter 50 value 84.892851
iter 60 value 83.301635
iter 70 value 81.003202
iter 80 value 80.605722
iter 90 value 80.427155
iter 100 value 80.260878
final value 80.260878
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 124.618256
iter 10 value 94.058596
iter 20 value 94.052724
iter 30 value 93.635324
iter 40 value 87.288996
iter 50 value 86.490585
iter 60 value 86.042658
iter 70 value 85.999881
iter 80 value 85.998413
iter 90 value 85.998174
iter 100 value 85.998109
final value 85.998109
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 103.397483
iter 10 value 94.046529
iter 20 value 94.039242
iter 30 value 89.766378
iter 40 value 86.288762
iter 50 value 85.371975
iter 60 value 85.363400
iter 70 value 84.949348
iter 80 value 84.946490
final value 84.939857
converged
Fitting Repeat 2
# weights: 507
initial value 96.763384
iter 10 value 94.046121
iter 20 value 94.038615
iter 30 value 93.377321
iter 40 value 91.285211
iter 50 value 91.206840
iter 60 value 91.205183
iter 70 value 90.476441
iter 80 value 90.458222
iter 90 value 90.072984
final value 90.062397
converged
Fitting Repeat 3
# weights: 507
initial value 93.117936
iter 10 value 88.606342
iter 20 value 87.988805
iter 30 value 87.837502
iter 40 value 87.836347
iter 50 value 87.803433
iter 60 value 87.798007
iter 60 value 87.798007
final value 87.798007
converged
Fitting Repeat 4
# weights: 507
initial value 103.124797
iter 10 value 94.060468
iter 20 value 94.052070
iter 30 value 87.397718
iter 40 value 83.999036
iter 50 value 82.353409
iter 60 value 80.047385
iter 70 value 80.037837
final value 80.037704
converged
Fitting Repeat 5
# weights: 507
initial value 104.073983
iter 10 value 94.046642
iter 20 value 94.027817
iter 30 value 93.810427
final value 93.810424
converged
Fitting Repeat 1
# weights: 103
initial value 124.760464
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 102.713036
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 100.845041
final value 92.211113
converged
Fitting Repeat 4
# weights: 103
initial value 100.311464
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 113.793450
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 96.095392
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 115.908939
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 94.519263
final value 93.915746
converged
Fitting Repeat 4
# weights: 305
initial value 97.027370
final value 93.915746
converged
Fitting Repeat 5
# weights: 305
initial value 113.869459
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 108.505195
final value 93.915746
converged
Fitting Repeat 2
# weights: 507
initial value 117.418487
iter 10 value 92.191089
final value 92.116925
converged
Fitting Repeat 3
# weights: 507
initial value 95.471588
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 122.102468
iter 10 value 93.288889
iter 10 value 93.288889
iter 10 value 93.288889
final value 93.288889
converged
Fitting Repeat 5
# weights: 507
initial value 96.423219
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 107.051902
iter 10 value 94.055138
iter 20 value 93.809998
iter 30 value 93.456360
iter 40 value 93.448658
iter 50 value 93.445785
iter 60 value 92.585801
iter 70 value 87.506931
iter 80 value 86.803527
iter 90 value 82.613117
iter 100 value 80.435025
final value 80.435025
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 95.909694
iter 10 value 94.055905
iter 20 value 93.848929
iter 30 value 93.471562
iter 40 value 93.441798
iter 50 value 86.592429
iter 60 value 86.199541
iter 70 value 84.759699
iter 80 value 83.138803
iter 90 value 83.122367
final value 83.122310
converged
Fitting Repeat 3
# weights: 103
initial value 102.887790
iter 10 value 94.121429
iter 20 value 94.046368
iter 30 value 93.605523
iter 40 value 88.794592
iter 50 value 81.577643
iter 60 value 81.398146
iter 70 value 81.368395
iter 80 value 79.705974
iter 90 value 79.211675
iter 100 value 79.090929
final value 79.090929
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 105.359802
iter 10 value 93.806722
iter 20 value 86.388294
iter 30 value 81.251961
iter 40 value 80.209723
iter 50 value 79.520087
iter 60 value 79.373062
iter 70 value 79.175914
iter 80 value 79.097115
final value 79.096282
converged
Fitting Repeat 5
# weights: 103
initial value 97.456410
iter 10 value 93.276785
iter 20 value 85.020120
iter 30 value 84.140942
iter 40 value 83.316697
iter 50 value 83.159059
iter 60 value 83.128559
final value 83.128265
converged
Fitting Repeat 1
# weights: 305
initial value 101.272110
iter 10 value 93.758596
iter 20 value 86.923477
iter 30 value 85.694090
iter 40 value 84.042983
iter 50 value 81.995188
iter 60 value 80.666618
iter 70 value 79.718017
iter 80 value 79.440269
iter 90 value 79.367654
iter 100 value 79.351139
final value 79.351139
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.817375
iter 10 value 91.431994
iter 20 value 86.967895
iter 30 value 86.078262
iter 40 value 85.878676
iter 50 value 85.278079
iter 60 value 84.690820
iter 70 value 83.723433
iter 80 value 81.479336
iter 90 value 80.671762
iter 100 value 80.612673
final value 80.612673
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 107.522314
iter 10 value 94.040303
iter 20 value 93.802919
iter 30 value 93.505133
iter 40 value 92.573055
iter 50 value 85.919465
iter 60 value 80.782937
iter 70 value 79.545717
iter 80 value 78.909154
iter 90 value 78.580836
iter 100 value 78.521667
final value 78.521667
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 113.260068
iter 10 value 93.913354
iter 20 value 89.907459
iter 30 value 87.573515
iter 40 value 85.915389
iter 50 value 84.289092
iter 60 value 82.928195
iter 70 value 81.597865
iter 80 value 80.463766
iter 90 value 78.350577
iter 100 value 77.864182
final value 77.864182
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 118.129225
iter 10 value 94.178896
iter 20 value 91.959161
iter 30 value 84.210497
iter 40 value 83.424573
iter 50 value 82.893850
iter 60 value 82.584007
iter 70 value 82.488701
iter 80 value 82.375717
iter 90 value 82.358747
iter 100 value 82.347657
final value 82.347657
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.143283
iter 10 value 94.074816
iter 20 value 90.813715
iter 30 value 85.005204
iter 40 value 82.376748
iter 50 value 80.238135
iter 60 value 78.407344
iter 70 value 77.741223
iter 80 value 77.495898
iter 90 value 77.356611
iter 100 value 77.149245
final value 77.149245
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.187143
iter 10 value 86.850028
iter 20 value 84.574043
iter 30 value 83.584498
iter 40 value 81.379633
iter 50 value 79.243860
iter 60 value 78.352932
iter 70 value 77.898390
iter 80 value 77.788704
iter 90 value 77.524304
iter 100 value 77.365045
final value 77.365045
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.851459
iter 10 value 94.204454
iter 20 value 87.673704
iter 30 value 84.837650
iter 40 value 82.826901
iter 50 value 81.783908
iter 60 value 80.697044
iter 70 value 79.916411
iter 80 value 79.831849
iter 90 value 79.650564
iter 100 value 79.434171
final value 79.434171
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.619070
iter 10 value 94.923319
iter 20 value 91.337436
iter 30 value 85.841735
iter 40 value 82.111319
iter 50 value 79.682435
iter 60 value 78.750319
iter 70 value 78.427403
iter 80 value 77.657733
iter 90 value 77.499550
iter 100 value 77.449434
final value 77.449434
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 118.545026
iter 10 value 93.586334
iter 20 value 83.318980
iter 30 value 81.113504
iter 40 value 79.943676
iter 50 value 78.660413
iter 60 value 78.445901
iter 70 value 78.292435
iter 80 value 78.181520
iter 90 value 78.048591
iter 100 value 77.963828
final value 77.963828
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 110.411439
iter 10 value 93.917759
iter 20 value 93.916056
iter 30 value 84.257641
iter 40 value 82.783510
iter 50 value 82.740344
iter 60 value 82.677922
iter 70 value 82.676874
iter 80 value 82.389712
final value 82.382518
converged
Fitting Repeat 2
# weights: 103
initial value 100.858670
final value 94.054320
converged
Fitting Repeat 3
# weights: 103
initial value 101.669643
final value 94.054557
converged
Fitting Repeat 4
# weights: 103
initial value 96.524974
final value 93.456737
converged
Fitting Repeat 5
# weights: 103
initial value 99.194173
final value 94.054598
converged
Fitting Repeat 1
# weights: 305
initial value 109.889218
iter 10 value 94.057833
iter 20 value 94.040655
iter 30 value 93.455137
iter 40 value 93.439734
final value 93.438810
converged
Fitting Repeat 2
# weights: 305
initial value 94.287163
iter 10 value 93.833539
iter 20 value 83.318773
iter 30 value 81.954465
iter 40 value 81.684524
iter 50 value 81.464448
iter 60 value 81.437742
iter 70 value 81.094029
iter 80 value 80.213212
iter 90 value 80.156872
iter 100 value 80.150992
final value 80.150992
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 96.724163
iter 10 value 93.920431
iter 20 value 93.800840
iter 30 value 88.374510
iter 40 value 84.143303
iter 50 value 84.124272
final value 84.124148
converged
Fitting Repeat 4
# weights: 305
initial value 97.590638
iter 10 value 94.057618
iter 20 value 93.845038
iter 30 value 93.439288
iter 40 value 93.373962
iter 50 value 93.373767
iter 50 value 93.373766
iter 50 value 93.373766
final value 93.373766
converged
Fitting Repeat 5
# weights: 305
initial value 101.084958
iter 10 value 81.425569
iter 20 value 80.708469
iter 30 value 80.705785
iter 40 value 80.616966
iter 50 value 80.614929
iter 60 value 80.421281
iter 70 value 80.419565
iter 80 value 80.418713
iter 90 value 80.413380
iter 100 value 80.383722
final value 80.383722
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 106.590050
iter 10 value 93.923394
iter 20 value 93.918097
iter 30 value 93.916833
iter 40 value 89.069968
iter 50 value 84.357921
iter 60 value 84.245527
iter 70 value 84.229380
iter 80 value 84.226870
final value 84.226847
converged
Fitting Repeat 2
# weights: 507
initial value 108.345920
iter 10 value 93.894237
iter 20 value 93.873996
iter 30 value 93.420044
iter 40 value 88.289624
iter 50 value 84.129283
iter 60 value 84.126040
iter 70 value 84.125235
iter 80 value 83.943618
iter 90 value 83.460612
iter 100 value 83.449279
final value 83.449279
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 108.234456
iter 10 value 93.297205
iter 20 value 93.296256
iter 30 value 90.582209
iter 40 value 82.462641
iter 50 value 82.279914
iter 60 value 82.254087
iter 70 value 82.253986
final value 82.253433
converged
Fitting Repeat 4
# weights: 507
initial value 96.630661
iter 10 value 93.469170
iter 20 value 93.399260
iter 30 value 93.396811
iter 40 value 90.727926
iter 50 value 85.388090
iter 60 value 85.387893
iter 70 value 85.277421
iter 80 value 85.276835
iter 90 value 85.274550
iter 100 value 85.119941
final value 85.119941
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 129.561255
iter 10 value 94.061205
iter 20 value 94.054285
iter 30 value 92.259749
iter 40 value 92.011844
iter 50 value 90.956659
final value 90.955249
converged
Fitting Repeat 1
# weights: 103
initial value 98.401187
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 102.353880
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 103.157994
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 100.725251
iter 10 value 94.461207
iter 10 value 94.461207
iter 10 value 94.461207
final value 94.461207
converged
Fitting Repeat 5
# weights: 103
initial value 100.119397
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 97.742304
final value 93.772973
converged
Fitting Repeat 2
# weights: 305
initial value 96.959279
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 105.979490
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 96.353445
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 97.073215
iter 10 value 94.484794
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 102.363582
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 103.623486
iter 10 value 93.564151
final value 93.540410
converged
Fitting Repeat 3
# weights: 507
initial value 92.636686
iter 10 value 86.909008
iter 20 value 86.766317
iter 30 value 86.765971
iter 40 value 86.765835
iter 40 value 86.765835
iter 40 value 86.765835
final value 86.765835
converged
Fitting Repeat 4
# weights: 507
initial value 100.752755
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 107.735823
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 105.133608
iter 10 value 94.339222
iter 20 value 87.014810
iter 30 value 84.839796
iter 40 value 84.527044
iter 50 value 84.170007
iter 60 value 83.851022
iter 70 value 83.822356
final value 83.822251
converged
Fitting Repeat 2
# weights: 103
initial value 97.302282
iter 10 value 94.537741
iter 20 value 94.487875
iter 30 value 94.383674
iter 40 value 93.960313
iter 50 value 93.901291
iter 60 value 93.815691
iter 70 value 88.736383
iter 80 value 82.715915
iter 90 value 82.010898
iter 100 value 81.699175
final value 81.699175
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.634761
iter 10 value 94.489995
iter 20 value 94.356771
iter 30 value 93.858801
iter 40 value 93.840625
iter 50 value 93.729198
iter 60 value 90.409276
iter 70 value 87.457901
iter 80 value 83.447256
iter 90 value 82.354185
iter 100 value 80.944360
final value 80.944360
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 98.080689
iter 10 value 94.500372
iter 20 value 92.665162
iter 30 value 84.609066
iter 40 value 83.956571
iter 50 value 83.870758
iter 60 value 82.965040
iter 70 value 82.608107
iter 80 value 82.261978
iter 90 value 81.600286
iter 100 value 81.147153
final value 81.147153
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 103.059900
iter 10 value 94.472954
iter 20 value 92.667416
iter 30 value 87.913633
iter 40 value 83.275165
iter 50 value 82.823037
iter 60 value 82.604366
iter 70 value 81.771137
iter 80 value 81.764290
final value 81.764288
converged
Fitting Repeat 1
# weights: 305
initial value 102.156075
iter 10 value 93.701426
iter 20 value 86.069510
iter 30 value 84.312628
iter 40 value 81.452257
iter 50 value 80.599822
iter 60 value 79.878990
iter 70 value 79.715466
iter 80 value 79.648728
iter 90 value 79.639298
iter 100 value 79.633609
final value 79.633609
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.428329
iter 10 value 94.236398
iter 20 value 93.675761
iter 30 value 88.686020
iter 40 value 84.920035
iter 50 value 83.859820
iter 60 value 83.547614
iter 70 value 83.390015
iter 80 value 83.057639
iter 90 value 81.556758
iter 100 value 79.986560
final value 79.986560
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.850214
iter 10 value 94.392944
iter 20 value 89.428603
iter 30 value 84.382604
iter 40 value 83.451595
iter 50 value 83.220966
iter 60 value 82.583241
iter 70 value 81.997692
iter 80 value 81.721784
iter 90 value 80.062440
iter 100 value 79.716360
final value 79.716360
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 107.283669
iter 10 value 94.361155
iter 20 value 93.775035
iter 30 value 90.124072
iter 40 value 84.663567
iter 50 value 83.978539
iter 60 value 81.159935
iter 70 value 79.738898
iter 80 value 79.222868
iter 90 value 79.119448
iter 100 value 79.054601
final value 79.054601
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 104.383114
iter 10 value 95.718121
iter 20 value 93.287400
iter 30 value 86.248450
iter 40 value 83.809990
iter 50 value 82.977856
iter 60 value 82.120121
iter 70 value 81.229124
iter 80 value 80.611974
iter 90 value 80.203402
iter 100 value 79.979709
final value 79.979709
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 120.375140
iter 10 value 94.765717
iter 20 value 84.963422
iter 30 value 83.981076
iter 40 value 82.278999
iter 50 value 81.614775
iter 60 value 81.514563
iter 70 value 81.269226
iter 80 value 80.869121
iter 90 value 79.757682
iter 100 value 79.483187
final value 79.483187
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 114.796286
iter 10 value 87.658863
iter 20 value 85.401673
iter 30 value 84.604551
iter 40 value 81.554776
iter 50 value 80.741177
iter 60 value 79.997328
iter 70 value 79.877511
iter 80 value 79.577355
iter 90 value 79.430239
iter 100 value 79.140918
final value 79.140918
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.260200
iter 10 value 96.946835
iter 20 value 94.413147
iter 30 value 92.462854
iter 40 value 91.215593
iter 50 value 83.975062
iter 60 value 83.309086
iter 70 value 82.143690
iter 80 value 80.731207
iter 90 value 80.361634
iter 100 value 80.152153
final value 80.152153
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 111.725277
iter 10 value 94.036906
iter 20 value 93.942124
iter 30 value 87.377901
iter 40 value 83.732351
iter 50 value 82.708322
iter 60 value 81.238062
iter 70 value 80.841504
iter 80 value 80.284552
iter 90 value 80.267257
iter 100 value 80.189421
final value 80.189421
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.108547
iter 10 value 94.586698
iter 20 value 94.079947
iter 30 value 88.656389
iter 40 value 87.004813
iter 50 value 83.735848
iter 60 value 81.638293
iter 70 value 81.048530
iter 80 value 79.782936
iter 90 value 79.026733
iter 100 value 78.843752
final value 78.843752
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.167712
iter 10 value 94.485679
iter 20 value 94.484225
iter 20 value 94.484225
iter 20 value 94.484225
final value 94.484225
converged
Fitting Repeat 2
# weights: 103
initial value 99.169687
iter 10 value 93.378684
iter 20 value 93.377341
final value 93.376562
converged
Fitting Repeat 3
# weights: 103
initial value 104.834328
final value 94.485799
converged
Fitting Repeat 4
# weights: 103
initial value 96.971324
final value 94.485782
converged
Fitting Repeat 5
# weights: 103
initial value 101.250763
final value 94.485849
converged
Fitting Repeat 1
# weights: 305
initial value 105.017391
iter 10 value 93.778244
iter 20 value 93.688040
iter 30 value 92.852302
iter 40 value 86.479715
iter 50 value 81.114236
iter 60 value 79.353548
iter 70 value 78.618911
iter 80 value 78.614483
iter 90 value 78.337442
iter 100 value 78.155847
final value 78.155847
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.043896
iter 10 value 93.778451
iter 20 value 93.776845
iter 30 value 93.441964
iter 40 value 84.568527
iter 50 value 81.684519
iter 60 value 81.374631
final value 81.268535
converged
Fitting Repeat 3
# weights: 305
initial value 108.735916
iter 10 value 94.493883
iter 20 value 94.488688
final value 94.488600
converged
Fitting Repeat 4
# weights: 305
initial value 100.762450
iter 10 value 94.489090
iter 20 value 94.315418
final value 93.773342
converged
Fitting Repeat 5
# weights: 305
initial value 117.000040
iter 10 value 89.552579
iter 20 value 86.101338
iter 30 value 86.094537
final value 86.093863
converged
Fitting Repeat 1
# weights: 507
initial value 100.125923
iter 10 value 86.312167
iter 20 value 85.902933
iter 30 value 85.428665
iter 40 value 85.426869
iter 50 value 84.999141
iter 60 value 81.054211
iter 70 value 80.320572
iter 80 value 79.885294
iter 90 value 79.882204
final value 79.881721
converged
Fitting Repeat 2
# weights: 507
initial value 95.450328
iter 10 value 88.031679
iter 20 value 86.171129
iter 30 value 83.874029
iter 40 value 82.859022
iter 50 value 82.350523
iter 60 value 81.960258
final value 81.959945
converged
Fitting Repeat 3
# weights: 507
initial value 111.641876
iter 10 value 94.492521
iter 20 value 94.366306
iter 30 value 85.260363
iter 40 value 81.980565
iter 50 value 81.965186
iter 60 value 81.964398
iter 70 value 81.963622
iter 80 value 81.611818
iter 90 value 80.763458
iter 100 value 79.335149
final value 79.335149
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 103.037601
iter 10 value 94.492783
iter 20 value 94.484111
iter 30 value 87.728291
iter 40 value 83.029965
iter 50 value 80.255594
iter 60 value 79.922943
iter 70 value 79.895700
iter 80 value 79.289805
iter 90 value 78.992722
final value 78.992550
converged
Fitting Repeat 5
# weights: 507
initial value 103.124242
iter 10 value 94.365879
iter 20 value 85.774335
iter 30 value 85.718407
iter 40 value 85.642892
iter 50 value 85.572168
final value 85.572087
converged
Fitting Repeat 1
# weights: 103
initial value 95.586351
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 107.042586
iter 10 value 92.607050
iter 20 value 92.552247
final value 92.552060
converged
Fitting Repeat 3
# weights: 103
initial value 95.677024
final value 94.466823
converged
Fitting Repeat 4
# weights: 103
initial value 101.581076
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 107.443663
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.486752
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 126.799729
iter 10 value 94.466827
final value 94.466823
converged
Fitting Repeat 3
# weights: 305
initial value 96.308352
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 115.333627
final value 94.466823
converged
Fitting Repeat 5
# weights: 305
initial value 130.742839
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 96.124173
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 94.873930
iter 10 value 89.211498
iter 20 value 84.546811
iter 30 value 81.722051
iter 40 value 81.495596
iter 50 value 81.472521
final value 81.472496
converged
Fitting Repeat 3
# weights: 507
initial value 108.238864
iter 10 value 93.800609
iter 20 value 92.763538
final value 92.763204
converged
Fitting Repeat 4
# weights: 507
initial value 107.902294
final value 94.466823
converged
Fitting Repeat 5
# weights: 507
initial value 107.229837
iter 10 value 93.997320
iter 20 value 93.946921
final value 93.946831
converged
Fitting Repeat 1
# weights: 103
initial value 104.048586
iter 10 value 91.572206
iter 20 value 85.801895
iter 30 value 84.368181
iter 40 value 84.089492
iter 50 value 83.906636
iter 60 value 83.570096
iter 70 value 82.108389
iter 80 value 81.835767
iter 90 value 81.832031
final value 81.832029
converged
Fitting Repeat 2
# weights: 103
initial value 100.131279
iter 10 value 95.318897
iter 20 value 94.494952
iter 30 value 93.549906
iter 40 value 85.434368
iter 50 value 85.340432
iter 60 value 84.478414
iter 70 value 84.066648
iter 80 value 83.951355
iter 90 value 83.927742
iter 100 value 83.801196
final value 83.801196
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 97.208042
iter 10 value 94.491155
iter 20 value 91.960376
iter 30 value 91.771460
iter 40 value 91.699808
final value 91.698937
converged
Fitting Repeat 4
# weights: 103
initial value 105.809417
iter 10 value 94.397866
iter 20 value 86.312137
iter 30 value 84.443260
iter 40 value 84.221870
iter 50 value 83.887272
iter 60 value 83.792686
final value 83.792570
converged
Fitting Repeat 5
# weights: 103
initial value 103.591611
iter 10 value 94.515083
iter 20 value 93.505525
iter 30 value 93.440975
iter 40 value 93.371152
iter 50 value 88.154109
iter 60 value 85.155728
iter 70 value 84.338245
iter 80 value 84.195723
iter 90 value 84.112529
iter 100 value 83.854131
final value 83.854131
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 108.326091
iter 10 value 94.457459
iter 20 value 87.106073
iter 30 value 85.824987
iter 40 value 85.180509
iter 50 value 82.268400
iter 60 value 81.153467
iter 70 value 81.073120
iter 80 value 80.968246
iter 90 value 80.762529
iter 100 value 80.591945
final value 80.591945
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.332797
iter 10 value 94.580496
iter 20 value 94.405756
iter 30 value 87.067948
iter 40 value 86.408210
iter 50 value 85.955236
iter 60 value 85.474489
iter 70 value 82.434125
iter 80 value 81.653902
iter 90 value 81.206799
iter 100 value 81.135300
final value 81.135300
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 130.045034
iter 10 value 93.883207
iter 20 value 86.114503
iter 30 value 85.297367
iter 40 value 84.130523
iter 50 value 82.568532
iter 60 value 82.262995
iter 70 value 82.089982
iter 80 value 81.840175
iter 90 value 81.080730
iter 100 value 80.790015
final value 80.790015
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 126.208534
iter 10 value 94.415015
iter 20 value 90.429792
iter 30 value 82.949002
iter 40 value 82.212538
iter 50 value 81.598431
iter 60 value 81.231571
iter 70 value 81.081433
iter 80 value 81.049876
iter 90 value 80.976720
iter 100 value 80.434042
final value 80.434042
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.149855
iter 10 value 94.518021
iter 20 value 94.479941
iter 30 value 88.670038
iter 40 value 87.530025
iter 50 value 85.260268
iter 60 value 84.627938
iter 70 value 83.196120
iter 80 value 82.965783
iter 90 value 82.788877
iter 100 value 82.400669
final value 82.400669
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.881216
iter 10 value 89.378909
iter 20 value 86.652089
iter 30 value 85.150297
iter 40 value 84.998641
iter 50 value 84.893233
iter 60 value 84.857358
iter 70 value 84.835075
iter 80 value 84.432262
iter 90 value 83.836908
iter 100 value 83.505390
final value 83.505390
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 115.442978
iter 10 value 95.051846
iter 20 value 94.534399
iter 30 value 92.897035
iter 40 value 88.614485
iter 50 value 84.999907
iter 60 value 82.331519
iter 70 value 81.622947
iter 80 value 81.222680
iter 90 value 80.909884
iter 100 value 80.435143
final value 80.435143
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.493048
iter 10 value 91.643393
iter 20 value 89.076912
iter 30 value 85.799306
iter 40 value 84.478836
iter 50 value 82.703335
iter 60 value 81.956412
iter 70 value 80.749846
iter 80 value 80.404578
iter 90 value 80.029718
iter 100 value 79.984553
final value 79.984553
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.391105
iter 10 value 94.439826
iter 20 value 89.062277
iter 30 value 87.747771
iter 40 value 86.903218
iter 50 value 84.605793
iter 60 value 83.425369
iter 70 value 81.263134
iter 80 value 81.041183
iter 90 value 80.522015
iter 100 value 80.312421
final value 80.312421
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 108.764892
iter 10 value 94.755884
iter 20 value 93.100772
iter 30 value 85.326428
iter 40 value 84.020342
iter 50 value 83.920954
iter 60 value 81.965938
iter 70 value 81.857970
iter 80 value 81.543680
iter 90 value 81.025962
iter 100 value 80.167648
final value 80.167648
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.808401
final value 94.485643
converged
Fitting Repeat 2
# weights: 103
initial value 110.328201
final value 94.485942
converged
Fitting Repeat 3
# weights: 103
initial value 96.902811
final value 94.485959
converged
Fitting Repeat 4
# weights: 103
initial value 95.055553
iter 10 value 93.890667
iter 20 value 93.294104
iter 30 value 93.292098
iter 40 value 93.291278
final value 93.290012
converged
Fitting Repeat 5
# weights: 103
initial value 100.684015
final value 94.485621
converged
Fitting Repeat 1
# weights: 305
initial value 101.001101
iter 10 value 94.489158
iter 20 value 94.376668
iter 30 value 93.487191
iter 40 value 93.413505
iter 50 value 93.211233
iter 60 value 93.209922
final value 93.209877
converged
Fitting Repeat 2
# weights: 305
initial value 104.915713
iter 10 value 94.434557
iter 20 value 94.433431
iter 30 value 94.307747
iter 40 value 92.321670
iter 50 value 91.865200
iter 60 value 91.863812
iter 70 value 91.862215
iter 80 value 88.884996
iter 90 value 82.320062
iter 100 value 82.132210
final value 82.132210
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 105.024963
iter 10 value 94.489052
iter 20 value 94.466502
iter 30 value 92.692701
iter 40 value 92.514070
final value 92.514003
converged
Fitting Repeat 4
# weights: 305
initial value 104.411910
iter 10 value 94.488673
iter 20 value 94.422889
iter 30 value 86.942250
iter 40 value 85.954931
iter 40 value 85.954930
iter 40 value 85.954930
final value 85.954930
converged
Fitting Repeat 5
# weights: 305
initial value 106.152196
iter 10 value 94.471807
iter 20 value 92.627059
iter 30 value 84.667622
iter 40 value 84.232420
final value 84.232419
converged
Fitting Repeat 1
# weights: 507
initial value 118.827949
iter 10 value 94.474479
iter 20 value 93.719764
iter 30 value 87.165363
iter 40 value 85.376137
iter 50 value 84.966090
iter 60 value 84.964304
iter 70 value 84.520445
final value 84.520380
converged
Fitting Repeat 2
# weights: 507
initial value 119.640621
iter 10 value 94.492584
iter 20 value 94.485007
iter 30 value 92.628026
iter 40 value 88.776948
iter 50 value 88.772292
iter 60 value 88.380087
iter 70 value 85.239366
iter 80 value 81.743694
iter 90 value 81.432893
iter 100 value 81.427860
final value 81.427860
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 113.257916
iter 10 value 94.474875
iter 20 value 94.318480
iter 30 value 86.115374
iter 40 value 84.719851
iter 50 value 82.792062
iter 60 value 82.781484
iter 70 value 82.780914
iter 80 value 82.561772
final value 82.561631
converged
Fitting Repeat 4
# weights: 507
initial value 96.291187
iter 10 value 89.019998
iter 20 value 84.895291
iter 30 value 84.801767
iter 40 value 84.721889
iter 50 value 84.692889
iter 60 value 84.178278
iter 70 value 84.146777
iter 80 value 84.146432
iter 90 value 83.404412
iter 100 value 82.955257
final value 82.955257
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 114.849527
iter 10 value 94.562244
iter 20 value 93.460577
iter 30 value 93.370997
iter 40 value 93.330223
iter 50 value 93.309682
iter 60 value 93.303989
iter 70 value 93.295293
iter 80 value 85.248132
iter 90 value 84.975683
iter 100 value 84.912675
final value 84.912675
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 120.276297
iter 10 value 117.508864
iter 20 value 117.506058
iter 30 value 105.882141
iter 40 value 103.456367
iter 50 value 103.393249
iter 60 value 103.280159
iter 70 value 103.238221
iter 80 value 103.237957
iter 90 value 103.237226
final value 103.237216
converged
Fitting Repeat 2
# weights: 507
initial value 172.035354
iter 10 value 117.766774
iter 20 value 117.623226
iter 30 value 117.512122
final value 117.511945
converged
Fitting Repeat 3
# weights: 507
initial value 129.725083
iter 10 value 117.767042
iter 20 value 117.103679
iter 30 value 110.985989
final value 110.921347
converged
Fitting Repeat 4
# weights: 507
initial value 125.350904
iter 10 value 117.897956
iter 20 value 117.808463
iter 30 value 117.060925
iter 40 value 113.720457
iter 50 value 113.717967
iter 60 value 113.558990
iter 70 value 113.398674
final value 113.351984
converged
Fitting Repeat 5
# weights: 507
initial value 126.449186
iter 10 value 117.796576
iter 20 value 117.135259
iter 30 value 116.957223
iter 40 value 109.701025
iter 50 value 105.820182
iter 60 value 105.545931
iter 70 value 105.448865
final value 105.447091
converged
svmRadial
ranger
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls < cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
Setting levels: control = Positive, case = Negative
Setting direction: controls > cases
RUNIT TEST PROTOCOL -- Mon Apr 15 23:55:02 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
40.929 1.832 44.141
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 34.518 | 0.776 | 35.296 | |
| FreqInteractors | 0.220 | 0.012 | 0.232 | |
| calculateAAC | 0.033 | 0.008 | 0.040 | |
| calculateAutocor | 0.310 | 0.016 | 0.326 | |
| calculateCTDC | 0.072 | 0.000 | 0.072 | |
| calculateCTDD | 0.566 | 0.000 | 0.565 | |
| calculateCTDT | 0.240 | 0.008 | 0.248 | |
| calculateCTriad | 0.337 | 0.024 | 0.361 | |
| calculateDC | 0.083 | 0.003 | 0.087 | |
| calculateF | 0.290 | 0.004 | 0.294 | |
| calculateKSAAP | 0.089 | 0.004 | 0.093 | |
| calculateQD_Sm | 1.629 | 0.032 | 1.669 | |
| calculateTC | 1.449 | 0.060 | 1.509 | |
| calculateTC_Sm | 0.281 | 0.008 | 0.289 | |
| corr_plot | 34.397 | 0.488 | 34.885 | |
| enrichfindP | 0.469 | 0.048 | 9.622 | |
| enrichfind_hp | 0.091 | 0.020 | 1.211 | |
| enrichplot | 0.325 | 0.027 | 0.353 | |
| filter_missing_values | 0.001 | 0.000 | 0.001 | |
| getFASTA | 0.527 | 0.025 | 4.353 | |
| getHPI | 0.001 | 0.000 | 0.000 | |
| get_negativePPI | 0.001 | 0.000 | 0.001 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0.002 | 0.000 | 0.001 | |
| plotPPI | 0.068 | 0.003 | 0.072 | |
| pred_ensembel | 13.456 | 0.560 | 10.701 | |
| var_imp | 35.452 | 0.972 | 36.425 | |