Matineh Rahmatbakhsh
| Snapshot Date: 2025-03-20 13:00 -0400 (Thu, 20 Mar 2025) |
| git_url: https://git.bioconductor.org/packages/HPiP |
| git_branch: RELEASE_3_20 |
| git_last_commit: ce9e305 |
| git_last_commit_date: 2024-10-29 11:04:11 -0400 (Tue, 29 Oct 2024) |
| Back to Multiple platform build/check report for BioC 3.20: simplified long |
|
This page was generated on 2025-03-24 12:06 -0400 (Mon, 24 Mar 2025).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4763 |
| palomino8 | Windows Server 2022 Datacenter | x64 | 4.4.3 (2025-02-28 ucrt) -- "Trophy Case" | 4494 |
| merida1 | macOS 12.7.5 Monterey | x86_64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4521 |
| kjohnson1 | macOS 13.6.6 Ventura | arm64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4448 |
| taishan | Linux (openEuler 24.03 LTS) | aarch64 | 4.4.3 (2025-02-28) -- "Trophy Case" | 4414 |
| 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 979/2289 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.12.0 (landing page) Matineh Rahmatbakhsh
| nebbiolo2 | Linux (Ubuntu 24.04.1 LTS) / x86_64 | OK | OK | OK | | ||||||||
| palomino8 | Windows Server 2022 Datacenter / x64 | OK | OK | OK | OK | | ||||||||
| merida1 | macOS 12.7.5 Monterey / x86_64 | OK | OK | OK | OK | | ||||||||
| kjohnson1 | macOS 13.6.6 Ventura / arm64 | OK | OK | OK | OK | | ||||||||
| taishan | Linux (openEuler 24.03 LTS) / aarch64 | OK | OK | OK | ||||||||||
|
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: 1.12.0 |
| Command: F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.12.0.tar.gz |
| StartedAt: 2025-03-21 02:31:30 -0400 (Fri, 21 Mar 2025) |
| EndedAt: 2025-03-21 02:37:17 -0400 (Fri, 21 Mar 2025) |
| EllapsedTime: 346.6 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD check --no-multiarch --install=check:HPiP.install-out.txt --library=F:\biocbuild\bbs-3.20-bioc\R\library --no-vignettes --timings HPiP_1.12.0.tar.gz
###
##############################################################################
##############################################################################
* using log directory 'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck'
* using R version 4.4.3 (2025-02-28 ucrt)
* using platform: x86_64-w64-mingw32
* R was compiled by
gcc.exe (GCC) 13.3.0
GNU Fortran (GCC) 13.3.0
* 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 '1.12.0'
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking whether package 'HPiP' can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking 'build' directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... NOTE
Package unavailable to check Rd xrefs: 'ftrCOOL'
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of 'data' directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking R/sysdata.rda ... OK
* checking files in 'vignettes' ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
var_imp 35.16 1.46 36.61
FSmethod 34.56 1.85 36.42
corr_plot 34.47 1.85 36.37
pred_ensembel 14.21 0.42 13.05
enrichfindP 0.75 0.09 13.77
* checking for unstated dependencies in 'tests' ... OK
* checking tests ...
Running 'runTests.R'
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking running R code from vignettes ... SKIPPED
* checking re-building of vignette outputs ... SKIPPED
* checking PDF version of manual ... OK
* DONE
Status: 3 NOTEs
See
'F:/biocbuild/bbs-3.20-bioc/meat/HPiP.Rcheck/00check.log'
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### F:\biocbuild\bbs-3.20-bioc\R\bin\R.exe CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library 'F:/biocbuild/bbs-3.20-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 4.4.3 (2025-02-28 ucrt) -- "Trophy Case"
Copyright (C) 2025 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 95.178187
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 97.868128
final value 94.400000
converged
Fitting Repeat 3
# weights: 103
initial value 99.700032
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 99.077698
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 105.974551
final value 94.484210
converged
Fitting Repeat 1
# weights: 305
initial value 101.474673
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 102.740664
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 101.349770
final value 94.466823
converged
Fitting Repeat 4
# weights: 305
initial value 97.740541
iter 10 value 85.440769
iter 20 value 83.789197
iter 30 value 83.783361
final value 83.783302
converged
Fitting Repeat 5
# weights: 305
initial value 100.142395
iter 10 value 93.982194
iter 20 value 93.935266
final value 93.935239
converged
Fitting Repeat 1
# weights: 507
initial value 117.770121
iter 10 value 94.484211
iter 10 value 94.484211
iter 10 value 94.484211
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 107.400652
iter 10 value 89.695896
iter 20 value 81.332111
iter 30 value 81.181906
iter 40 value 81.176188
iter 50 value 81.158580
final value 81.144105
converged
Fitting Repeat 3
# weights: 507
initial value 99.861512
iter 10 value 92.148621
iter 20 value 91.960649
final value 91.960591
converged
Fitting Repeat 4
# weights: 507
initial value 111.264941
final value 94.484211
converged
Fitting Repeat 5
# weights: 507
initial value 111.542808
iter 10 value 94.299937
final value 94.299824
converged
Fitting Repeat 1
# weights: 103
initial value 104.152985
iter 10 value 94.478629
iter 20 value 85.319700
iter 30 value 83.964553
iter 40 value 83.906631
iter 50 value 83.869191
iter 60 value 83.270084
iter 70 value 83.036693
final value 83.036059
converged
Fitting Repeat 2
# weights: 103
initial value 97.300220
iter 10 value 94.531248
final value 94.488541
converged
Fitting Repeat 3
# weights: 103
initial value 101.801181
iter 10 value 94.508351
iter 20 value 94.487127
iter 30 value 94.455015
iter 40 value 94.015609
iter 50 value 89.992545
iter 60 value 84.936624
iter 70 value 83.878012
iter 80 value 83.231174
iter 90 value 83.096049
iter 100 value 83.093598
final value 83.093598
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 97.502349
iter 10 value 94.356231
iter 20 value 91.028120
iter 30 value 88.749227
iter 40 value 84.559991
iter 50 value 84.066654
iter 60 value 83.327797
iter 70 value 83.109604
iter 80 value 83.093620
final value 83.093595
converged
Fitting Repeat 5
# weights: 103
initial value 100.446996
iter 10 value 94.489292
iter 20 value 94.163224
iter 30 value 86.980051
iter 40 value 86.431272
iter 50 value 86.126423
iter 60 value 85.941007
iter 70 value 83.693967
iter 80 value 83.110186
final value 83.093596
converged
Fitting Repeat 1
# weights: 305
initial value 105.980765
iter 10 value 94.489065
iter 20 value 94.242803
iter 30 value 93.919387
iter 40 value 92.071700
iter 50 value 85.138184
iter 60 value 83.858120
iter 70 value 83.336743
iter 80 value 82.649885
iter 90 value 82.505016
iter 100 value 80.890118
final value 80.890118
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 99.313369
iter 10 value 94.352932
iter 20 value 89.682088
iter 30 value 83.806266
iter 40 value 83.034351
iter 50 value 82.684164
iter 60 value 82.582519
iter 70 value 82.354195
iter 80 value 81.991270
iter 90 value 81.802789
iter 100 value 81.669545
final value 81.669545
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 125.154345
iter 10 value 93.719593
iter 20 value 89.805611
iter 30 value 84.126321
iter 40 value 81.599641
iter 50 value 80.821167
iter 60 value 80.540239
iter 70 value 80.451710
iter 80 value 80.319169
iter 90 value 80.296844
iter 100 value 80.262528
final value 80.262528
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.614795
iter 10 value 92.532260
iter 20 value 88.730689
iter 30 value 85.788699
iter 40 value 85.581768
iter 50 value 84.049798
iter 60 value 80.054330
iter 70 value 78.842954
iter 80 value 78.462375
iter 90 value 78.311605
iter 100 value 78.253851
final value 78.253851
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 103.086828
iter 10 value 91.263037
iter 20 value 85.138393
iter 30 value 84.577699
iter 40 value 84.088305
iter 50 value 83.363200
iter 60 value 82.975045
iter 70 value 82.584999
iter 80 value 82.328033
iter 90 value 81.061987
iter 100 value 80.116788
final value 80.116788
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 112.025141
iter 10 value 94.495627
iter 20 value 94.164653
iter 30 value 85.002980
iter 40 value 83.811751
iter 50 value 82.849435
iter 60 value 82.738646
iter 70 value 82.511170
iter 80 value 81.492693
iter 90 value 80.630541
iter 100 value 80.144775
final value 80.144775
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.259577
iter 10 value 94.431478
iter 20 value 89.858307
iter 30 value 86.985459
iter 40 value 86.100262
iter 50 value 85.432435
iter 60 value 84.779166
iter 70 value 81.859102
iter 80 value 79.911192
iter 90 value 78.996199
iter 100 value 78.836241
final value 78.836241
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 117.737978
iter 10 value 94.238464
iter 20 value 86.171230
iter 30 value 84.097868
iter 40 value 83.612829
iter 50 value 80.435864
iter 60 value 79.887997
iter 70 value 79.633701
iter 80 value 79.384148
iter 90 value 79.119458
iter 100 value 79.051356
final value 79.051356
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.553825
iter 10 value 94.542356
iter 20 value 86.949833
iter 30 value 84.625321
iter 40 value 82.713997
iter 50 value 81.895277
iter 60 value 80.863013
iter 70 value 80.212245
iter 80 value 80.025385
iter 90 value 79.120429
iter 100 value 78.494787
final value 78.494787
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 111.226692
iter 10 value 94.546614
iter 20 value 91.828272
iter 30 value 83.739302
iter 40 value 82.417282
iter 50 value 81.262692
iter 60 value 80.630778
iter 70 value 80.248617
iter 80 value 79.936370
iter 90 value 79.297323
iter 100 value 78.964276
final value 78.964276
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 102.409667
final value 94.485853
converged
Fitting Repeat 2
# weights: 103
initial value 97.457428
iter 10 value 94.485864
final value 94.484297
converged
Fitting Repeat 3
# weights: 103
initial value 103.737357
final value 94.485741
converged
Fitting Repeat 4
# weights: 103
initial value 111.899576
final value 94.485542
converged
Fitting Repeat 5
# weights: 103
initial value 96.112800
final value 94.485962
converged
Fitting Repeat 1
# weights: 305
initial value 97.265973
iter 10 value 94.489423
iter 20 value 93.788643
iter 30 value 93.786858
iter 40 value 83.470728
final value 83.378766
converged
Fitting Repeat 2
# weights: 305
initial value 98.520516
iter 10 value 94.489049
iter 20 value 94.276183
iter 30 value 92.314003
iter 40 value 82.402547
iter 50 value 81.825250
iter 60 value 81.724320
final value 81.724226
converged
Fitting Repeat 3
# weights: 305
initial value 98.525496
iter 10 value 94.149887
iter 20 value 94.015041
iter 30 value 93.747584
iter 40 value 85.771466
iter 50 value 85.446133
iter 60 value 85.422031
final value 85.416268
converged
Fitting Repeat 4
# weights: 305
initial value 108.069361
final value 94.489099
converged
Fitting Repeat 5
# weights: 305
initial value 100.739452
iter 10 value 94.489031
iter 20 value 94.484221
iter 20 value 94.484221
final value 94.484221
converged
Fitting Repeat 1
# weights: 507
initial value 95.459965
iter 10 value 94.475067
iter 20 value 94.395118
iter 30 value 87.941526
iter 40 value 84.822827
final value 84.815244
converged
Fitting Repeat 2
# weights: 507
initial value 98.936139
iter 10 value 94.474956
iter 20 value 94.400596
iter 30 value 91.715914
iter 40 value 87.100702
iter 50 value 87.100502
iter 60 value 86.890131
final value 86.888969
converged
Fitting Repeat 3
# weights: 507
initial value 115.203004
iter 10 value 94.492245
iter 20 value 94.365655
iter 30 value 84.359482
iter 40 value 84.358432
iter 50 value 83.937885
iter 60 value 81.206179
iter 70 value 79.613265
iter 80 value 79.482224
iter 90 value 79.472641
iter 100 value 79.472515
final value 79.472515
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 95.093127
iter 10 value 94.060104
iter 20 value 93.979167
iter 30 value 84.247533
iter 40 value 83.833708
iter 50 value 82.689356
iter 60 value 82.551181
iter 70 value 82.550017
iter 80 value 82.549766
final value 82.549556
converged
Fitting Repeat 5
# weights: 507
initial value 101.417159
iter 10 value 94.492866
iter 20 value 94.441866
iter 30 value 85.551166
iter 40 value 83.406398
iter 50 value 83.397374
iter 60 value 83.377094
iter 70 value 83.368014
iter 80 value 82.011927
iter 90 value 81.318505
iter 100 value 81.250474
final value 81.250474
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.296289
iter 10 value 94.472208
final value 94.466823
converged
Fitting Repeat 2
# weights: 103
initial value 97.584147
final value 94.466823
converged
Fitting Repeat 3
# weights: 103
initial value 109.253625
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 102.509511
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 94.542842
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 98.770619
iter 10 value 93.941305
iter 10 value 93.941305
iter 10 value 93.941305
final value 93.941305
converged
Fitting Repeat 2
# weights: 305
initial value 96.618198
final value 94.484211
converged
Fitting Repeat 3
# weights: 305
initial value 94.725985
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 107.086928
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 99.115731
final value 94.466823
converged
Fitting Repeat 1
# weights: 507
initial value 105.437638
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 98.864213
final value 94.466823
converged
Fitting Repeat 3
# weights: 507
initial value 103.288332
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 94.252277
iter 10 value 83.811637
iter 20 value 83.380647
iter 30 value 83.281483
final value 83.281468
converged
Fitting Repeat 5
# weights: 507
initial value 124.235235
final value 94.484211
converged
Fitting Repeat 1
# weights: 103
initial value 99.860867
iter 10 value 94.456131
iter 20 value 93.483686
iter 30 value 85.337410
iter 40 value 84.015127
iter 50 value 83.770027
iter 60 value 83.416806
iter 70 value 83.102596
iter 80 value 82.423412
iter 90 value 81.767695
iter 100 value 81.516796
final value 81.516796
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 97.892527
iter 10 value 94.468028
iter 20 value 86.508076
iter 30 value 84.295870
iter 40 value 83.722945
iter 50 value 83.286220
iter 60 value 82.799907
iter 70 value 82.460710
iter 80 value 82.166392
iter 90 value 81.818824
iter 100 value 81.746311
final value 81.746311
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.178185
iter 10 value 94.487716
iter 20 value 93.978086
iter 30 value 86.922102
iter 40 value 84.973551
iter 50 value 84.643748
iter 60 value 84.461677
iter 70 value 84.272621
iter 80 value 84.167845
final value 84.163312
converged
Fitting Repeat 4
# weights: 103
initial value 98.799622
iter 10 value 90.974466
iter 20 value 84.799963
iter 30 value 84.270099
iter 40 value 84.086671
iter 50 value 83.997034
iter 60 value 83.952958
final value 83.951675
converged
Fitting Repeat 5
# weights: 103
initial value 98.617435
iter 10 value 94.401799
iter 20 value 88.129098
iter 30 value 87.101293
iter 40 value 86.561426
iter 50 value 86.323979
iter 60 value 83.634487
iter 70 value 83.566947
iter 80 value 83.508129
iter 90 value 83.490989
iter 100 value 83.440059
final value 83.440059
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 108.648135
iter 10 value 93.454778
iter 20 value 84.655549
iter 30 value 84.604671
iter 40 value 84.448236
iter 50 value 84.287797
iter 60 value 84.130850
iter 70 value 83.436773
iter 80 value 82.148960
iter 90 value 80.536198
iter 100 value 80.473546
final value 80.473546
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 101.490593
iter 10 value 94.531219
iter 20 value 85.351694
iter 30 value 85.023644
iter 40 value 84.421649
iter 50 value 82.854934
iter 60 value 81.190836
iter 70 value 80.566946
iter 80 value 80.422332
iter 90 value 80.301693
iter 100 value 80.067706
final value 80.067706
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 99.660076
iter 10 value 94.310588
iter 20 value 94.249240
iter 30 value 88.501778
iter 40 value 84.886745
iter 50 value 84.554486
iter 60 value 84.263449
iter 70 value 84.079526
iter 80 value 83.684200
iter 90 value 83.349860
iter 100 value 82.417561
final value 82.417561
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 104.133250
iter 10 value 95.597516
iter 20 value 92.518222
iter 30 value 92.383618
iter 40 value 92.129806
iter 50 value 89.982929
iter 60 value 87.442932
iter 70 value 84.197391
iter 80 value 83.688905
iter 90 value 83.607651
iter 100 value 83.367249
final value 83.367249
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 110.242813
iter 10 value 94.487319
iter 20 value 94.445224
iter 30 value 93.789346
iter 40 value 92.211577
iter 50 value 85.038053
iter 60 value 84.167149
iter 70 value 82.941339
iter 80 value 81.962948
iter 90 value 81.805475
iter 100 value 80.878974
final value 80.878974
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.714075
iter 10 value 91.148654
iter 20 value 86.745242
iter 30 value 86.609361
iter 40 value 83.998989
iter 50 value 82.600318
iter 60 value 81.346766
iter 70 value 80.560100
iter 80 value 80.436417
iter 90 value 80.403660
iter 100 value 80.395817
final value 80.395817
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.118276
iter 10 value 94.357793
iter 20 value 86.196642
iter 30 value 84.881628
iter 40 value 83.731891
iter 50 value 81.897072
iter 60 value 81.084442
iter 70 value 80.741779
iter 80 value 80.523067
iter 90 value 80.054588
iter 100 value 79.869444
final value 79.869444
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 122.073406
iter 10 value 95.089979
iter 20 value 87.528520
iter 30 value 84.935935
iter 40 value 84.586600
iter 50 value 84.273505
iter 60 value 83.979026
iter 70 value 83.551650
iter 80 value 82.540872
iter 90 value 81.976025
iter 100 value 81.854986
final value 81.854986
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.117705
iter 10 value 94.363029
iter 20 value 87.757545
iter 30 value 84.597160
iter 40 value 83.248757
iter 50 value 82.453119
iter 60 value 82.170506
iter 70 value 81.953631
iter 80 value 81.630331
iter 90 value 80.713621
iter 100 value 80.223555
final value 80.223555
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 107.036589
iter 10 value 94.424119
iter 20 value 87.220058
iter 30 value 86.176594
iter 40 value 84.389207
iter 50 value 83.927889
iter 60 value 83.873289
iter 70 value 82.566070
iter 80 value 81.797711
iter 90 value 81.184156
iter 100 value 81.065693
final value 81.065693
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.961332
iter 10 value 94.485797
iter 20 value 94.482521
iter 30 value 94.385703
iter 40 value 94.258975
final value 94.214055
converged
Fitting Repeat 2
# weights: 103
initial value 101.593003
final value 94.485965
converged
Fitting Repeat 3
# weights: 103
initial value 99.655481
final value 94.485794
converged
Fitting Repeat 4
# weights: 103
initial value 107.698793
iter 10 value 94.485643
iter 20 value 94.466776
iter 30 value 93.980774
iter 40 value 91.186356
final value 91.177436
converged
Fitting Repeat 5
# weights: 103
initial value 114.591636
final value 94.486096
converged
Fitting Repeat 1
# weights: 305
initial value 95.826301
iter 10 value 88.481170
iter 20 value 88.143439
iter 30 value 87.774925
iter 40 value 87.494513
iter 50 value 87.488791
final value 87.488527
converged
Fitting Repeat 2
# weights: 305
initial value 96.288818
iter 10 value 94.494321
iter 20 value 91.780835
iter 30 value 83.646103
iter 40 value 82.964876
iter 50 value 82.841762
iter 60 value 82.756526
iter 70 value 82.600650
iter 80 value 81.303004
iter 90 value 80.583555
iter 100 value 80.252174
final value 80.252174
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 96.666270
iter 10 value 94.471708
iter 20 value 92.682442
iter 30 value 84.621204
iter 40 value 83.714728
iter 50 value 83.692174
final value 83.692077
converged
Fitting Repeat 4
# weights: 305
initial value 95.967401
iter 10 value 94.248826
iter 20 value 94.217783
iter 30 value 92.732359
iter 40 value 85.241905
iter 50 value 85.036051
iter 60 value 85.028833
iter 70 value 85.004330
final value 84.994900
converged
Fitting Repeat 5
# weights: 305
initial value 101.775788
iter 10 value 94.619733
iter 20 value 94.484558
iter 30 value 94.215920
final value 94.214249
converged
Fitting Repeat 1
# weights: 507
initial value 98.958099
iter 10 value 94.178727
iter 20 value 94.164049
iter 30 value 88.225212
iter 40 value 83.060836
iter 50 value 82.628912
iter 60 value 82.531366
iter 70 value 82.141964
iter 80 value 82.025928
iter 90 value 82.025297
final value 82.025004
converged
Fitting Repeat 2
# weights: 507
initial value 114.690599
iter 10 value 94.492320
iter 20 value 94.455872
iter 30 value 92.856847
iter 40 value 92.812008
iter 50 value 89.133577
iter 60 value 83.956029
iter 70 value 83.949590
iter 80 value 83.536421
iter 90 value 83.466136
iter 100 value 83.459100
final value 83.459100
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.159742
iter 10 value 94.347565
iter 20 value 94.345405
iter 30 value 94.338103
iter 40 value 85.916930
iter 50 value 82.961262
iter 60 value 82.958780
final value 82.958709
converged
Fitting Repeat 4
# weights: 507
initial value 119.281140
iter 10 value 94.475049
iter 20 value 94.245387
iter 30 value 89.088528
iter 40 value 88.262504
iter 50 value 85.271271
iter 60 value 85.101083
iter 70 value 85.096836
iter 80 value 85.092277
iter 90 value 85.029941
iter 100 value 84.987749
final value 84.987749
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 100.395455
iter 10 value 94.488655
iter 20 value 92.044793
iter 30 value 83.012454
iter 40 value 82.933840
iter 50 value 81.861280
iter 60 value 81.813628
iter 70 value 81.806210
iter 80 value 81.804842
iter 90 value 81.701697
iter 100 value 81.681461
final value 81.681461
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.345969
iter 10 value 93.328263
iter 10 value 93.328262
iter 10 value 93.328262
final value 93.328262
converged
Fitting Repeat 2
# weights: 103
initial value 96.850345
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 99.083820
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 98.219053
final value 93.860363
converged
Fitting Repeat 5
# weights: 103
initial value 101.721210
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 94.429402
final value 94.052874
converged
Fitting Repeat 2
# weights: 305
initial value 118.732668
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 105.640890
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 112.442441
final value 94.052910
converged
Fitting Repeat 5
# weights: 305
initial value 101.245524
final value 94.052907
converged
Fitting Repeat 1
# weights: 507
initial value 98.371238
iter 10 value 84.051812
iter 20 value 83.825766
iter 30 value 83.816107
iter 40 value 83.791704
iter 50 value 83.728842
iter 60 value 83.705556
iter 60 value 83.705556
iter 60 value 83.705556
final value 83.705556
converged
Fitting Repeat 2
# weights: 507
initial value 114.667569
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 104.515027
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 94.831942
iter 10 value 86.300941
iter 20 value 86.021362
iter 30 value 86.018728
final value 86.018717
converged
Fitting Repeat 5
# weights: 507
initial value 104.853551
iter 10 value 84.113150
iter 20 value 83.656404
final value 83.627418
converged
Fitting Repeat 1
# weights: 103
initial value 98.382804
iter 10 value 93.943177
iter 20 value 89.928079
iter 30 value 85.462095
iter 40 value 83.846840
iter 50 value 81.587905
iter 60 value 81.364848
iter 70 value 80.983109
iter 80 value 80.639670
iter 90 value 80.633004
iter 100 value 80.628045
final value 80.628045
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 99.261996
iter 10 value 94.045502
iter 20 value 93.143058
iter 30 value 90.632696
iter 40 value 85.257854
iter 50 value 83.815483
iter 60 value 81.232545
iter 70 value 80.988410
iter 80 value 80.660389
iter 90 value 80.375470
final value 80.372091
converged
Fitting Repeat 3
# weights: 103
initial value 104.009077
iter 10 value 94.056740
iter 20 value 90.992201
iter 30 value 83.508547
iter 40 value 83.341392
iter 50 value 83.237008
iter 60 value 83.211576
final value 83.209253
converged
Fitting Repeat 4
# weights: 103
initial value 100.546324
iter 10 value 94.482877
iter 20 value 93.707369
iter 30 value 90.713780
iter 40 value 90.649807
iter 50 value 89.751029
iter 60 value 86.205894
iter 70 value 83.627288
iter 80 value 83.506137
iter 90 value 83.261618
iter 100 value 83.212804
final value 83.212804
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 98.135768
iter 10 value 94.044197
iter 20 value 93.573124
iter 30 value 85.587079
iter 40 value 83.533050
iter 50 value 83.301329
iter 60 value 83.076601
iter 70 value 83.015195
iter 80 value 83.004081
iter 90 value 82.982276
final value 82.979048
converged
Fitting Repeat 1
# weights: 305
initial value 100.960509
iter 10 value 94.063154
iter 20 value 85.533161
iter 30 value 83.571557
iter 40 value 82.908077
iter 50 value 82.840468
final value 82.832179
converged
Fitting Repeat 2
# weights: 305
initial value 114.001231
iter 10 value 93.992049
iter 20 value 93.787785
iter 30 value 91.238731
iter 40 value 85.916757
iter 50 value 84.776621
iter 60 value 83.369753
iter 70 value 82.882286
iter 80 value 81.668407
iter 90 value 80.308590
iter 100 value 79.813318
final value 79.813318
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.940124
iter 10 value 94.067191
iter 20 value 85.723315
iter 30 value 83.686086
iter 40 value 83.075188
iter 50 value 82.869076
iter 60 value 82.024786
iter 70 value 80.425676
iter 80 value 80.000586
iter 90 value 79.412747
iter 100 value 79.001539
final value 79.001539
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.037046
iter 10 value 94.217257
iter 20 value 93.817231
iter 30 value 83.760201
iter 40 value 83.179180
iter 50 value 82.258898
iter 60 value 81.379311
iter 70 value 80.759473
iter 80 value 80.618386
iter 90 value 80.549705
iter 100 value 80.462334
final value 80.462334
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 105.224808
iter 10 value 93.765380
iter 20 value 93.205184
iter 30 value 85.228925
iter 40 value 81.988451
iter 50 value 80.877871
iter 60 value 80.144744
iter 70 value 79.776351
iter 80 value 79.650580
iter 90 value 79.486266
iter 100 value 79.143956
final value 79.143956
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 125.300634
iter 10 value 95.562171
iter 20 value 87.326297
iter 30 value 83.599147
iter 40 value 82.231183
iter 50 value 81.378897
iter 60 value 80.920896
iter 70 value 80.525565
iter 80 value 79.772949
iter 90 value 78.968327
iter 100 value 78.834685
final value 78.834685
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.390716
iter 10 value 94.348301
iter 20 value 90.960363
iter 30 value 88.809534
iter 40 value 82.056781
iter 50 value 81.216589
iter 60 value 80.745913
iter 70 value 80.024878
iter 80 value 79.211714
iter 90 value 78.833191
iter 100 value 78.743886
final value 78.743886
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.281752
iter 10 value 96.169972
iter 20 value 93.915272
iter 30 value 87.798140
iter 40 value 85.853552
iter 50 value 83.183380
iter 60 value 81.617064
iter 70 value 80.979625
iter 80 value 79.534557
iter 90 value 79.293579
iter 100 value 79.170579
final value 79.170579
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 115.877243
iter 10 value 94.404953
iter 20 value 86.027138
iter 30 value 84.432743
iter 40 value 83.158556
iter 50 value 81.034120
iter 60 value 80.478702
iter 70 value 79.698365
iter 80 value 79.308853
iter 90 value 79.287561
iter 100 value 79.209757
final value 79.209757
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 104.943421
iter 10 value 93.549495
iter 20 value 85.847996
iter 30 value 82.056287
iter 40 value 81.815723
iter 50 value 81.150267
iter 60 value 81.002829
iter 70 value 80.987802
iter 80 value 80.880838
iter 90 value 80.748108
iter 100 value 80.394632
final value 80.394632
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.843924
final value 94.054580
converged
Fitting Repeat 2
# weights: 103
initial value 94.411209
final value 94.054875
converged
Fitting Repeat 3
# weights: 103
initial value 97.343035
final value 94.054692
converged
Fitting Repeat 4
# weights: 103
initial value 94.289022
final value 94.054687
converged
Fitting Repeat 5
# weights: 103
initial value 105.824721
final value 94.054696
converged
Fitting Repeat 1
# weights: 305
initial value 105.585367
iter 10 value 93.361401
iter 20 value 93.334449
iter 30 value 92.647660
iter 40 value 91.860539
iter 50 value 82.360619
final value 82.109013
converged
Fitting Repeat 2
# weights: 305
initial value 95.472526
iter 10 value 94.057935
final value 94.053190
converged
Fitting Repeat 3
# weights: 305
initial value 95.587601
iter 10 value 93.333574
iter 20 value 93.331979
iter 30 value 93.328298
iter 40 value 93.284035
iter 50 value 93.261989
iter 60 value 93.261954
iter 60 value 93.261953
iter 60 value 93.261953
final value 93.261953
converged
Fitting Repeat 4
# weights: 305
initial value 108.659870
iter 10 value 93.065309
iter 20 value 92.095918
iter 30 value 92.073536
iter 40 value 88.248855
iter 50 value 87.993609
iter 60 value 87.506327
iter 70 value 87.502882
iter 80 value 87.501799
iter 90 value 87.501444
iter 100 value 83.503402
final value 83.503402
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 95.008789
iter 10 value 93.839165
iter 20 value 93.813946
iter 30 value 93.005812
iter 40 value 87.146681
iter 50 value 85.659776
iter 60 value 85.318587
iter 70 value 85.297144
iter 80 value 85.286603
iter 90 value 81.889516
iter 100 value 81.858562
final value 81.858562
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 109.004025
iter 10 value 93.336815
iter 20 value 93.335439
iter 30 value 91.576624
iter 40 value 90.538666
iter 50 value 89.765365
iter 60 value 88.014865
iter 70 value 85.180767
iter 80 value 84.035555
iter 90 value 84.025042
iter 100 value 84.024759
final value 84.024759
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 97.613170
iter 10 value 93.336578
iter 20 value 93.328576
iter 30 value 85.068073
iter 40 value 84.766261
iter 50 value 81.335853
iter 60 value 79.796619
iter 70 value 78.995466
iter 80 value 78.879861
iter 90 value 78.805461
iter 100 value 78.805026
final value 78.805026
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 99.924748
iter 10 value 93.335021
iter 20 value 93.271010
iter 30 value 89.643459
iter 40 value 85.556235
iter 50 value 83.971121
iter 60 value 83.883263
iter 70 value 83.852583
iter 80 value 83.850085
iter 90 value 83.770791
iter 100 value 83.750063
final value 83.750063
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 94.936756
iter 10 value 93.336599
iter 20 value 93.331560
iter 30 value 93.318780
iter 40 value 93.272655
final value 93.272616
converged
Fitting Repeat 5
# weights: 507
initial value 105.506773
iter 10 value 93.759980
iter 20 value 93.469709
iter 30 value 93.467937
iter 40 value 93.302665
iter 50 value 93.264851
iter 60 value 93.261574
iter 70 value 93.162480
iter 80 value 91.429497
iter 90 value 90.773931
iter 100 value 90.771447
final value 90.771447
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 96.524541
final value 94.052910
converged
Fitting Repeat 2
# weights: 103
initial value 94.637612
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 100.162940
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 96.910879
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 100.030687
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 108.072576
final value 94.052910
converged
Fitting Repeat 2
# weights: 305
initial value 95.625945
final value 93.915746
converged
Fitting Repeat 3
# weights: 305
initial value 118.231267
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 95.268110
final value 93.913920
converged
Fitting Repeat 5
# weights: 305
initial value 91.340349
iter 10 value 87.488113
final value 87.487179
converged
Fitting Repeat 1
# weights: 507
initial value 136.757826
final value 93.628453
converged
Fitting Repeat 2
# weights: 507
initial value 102.623239
final value 94.052910
converged
Fitting Repeat 3
# weights: 507
initial value 104.674326
final value 93.913919
converged
Fitting Repeat 4
# weights: 507
initial value 94.182349
iter 10 value 92.933043
iter 20 value 92.693164
iter 30 value 92.692687
iter 30 value 92.692686
iter 30 value 92.692686
final value 92.692686
converged
Fitting Repeat 5
# weights: 507
initial value 115.730814
final value 94.052910
converged
Fitting Repeat 1
# weights: 103
initial value 107.812155
iter 10 value 93.435744
iter 20 value 86.350447
iter 30 value 83.908442
iter 40 value 83.491348
iter 50 value 82.248831
iter 60 value 81.936765
iter 70 value 81.822339
iter 70 value 81.822338
iter 70 value 81.822338
final value 81.822338
converged
Fitting Repeat 2
# weights: 103
initial value 96.751911
iter 10 value 94.064040
iter 20 value 93.826371
iter 30 value 92.435335
iter 40 value 88.736024
iter 50 value 84.032882
iter 60 value 83.627095
iter 70 value 83.496711
iter 80 value 82.293820
iter 90 value 81.776221
iter 100 value 81.647516
final value 81.647516
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 96.228561
iter 10 value 92.205310
iter 20 value 91.802983
iter 30 value 91.504821
iter 40 value 91.335675
iter 50 value 91.305609
iter 60 value 91.297524
iter 60 value 91.297524
final value 91.297524
converged
Fitting Repeat 4
# weights: 103
initial value 101.713187
iter 10 value 96.292032
iter 20 value 94.056579
iter 30 value 91.269095
iter 40 value 86.982950
iter 50 value 86.001173
iter 60 value 85.495991
iter 70 value 85.174214
iter 80 value 84.064615
iter 90 value 83.975157
final value 83.974066
converged
Fitting Repeat 5
# weights: 103
initial value 102.103256
iter 10 value 94.054829
iter 20 value 92.775346
iter 30 value 85.905240
iter 40 value 85.147198
iter 50 value 84.965690
iter 60 value 84.394496
iter 70 value 84.129048
iter 80 value 83.946258
iter 90 value 83.663268
iter 100 value 83.544041
final value 83.544041
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 104.274656
iter 10 value 94.154713
iter 20 value 93.212445
iter 30 value 85.554831
iter 40 value 85.374210
iter 50 value 84.662558
iter 60 value 83.909654
iter 70 value 83.804771
iter 80 value 83.755762
iter 90 value 83.214714
iter 100 value 81.234590
final value 81.234590
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 102.334265
iter 10 value 92.906785
iter 20 value 86.351631
iter 30 value 84.600207
iter 40 value 83.868816
iter 50 value 83.329093
iter 60 value 82.165630
iter 70 value 81.852265
iter 80 value 81.505260
iter 90 value 81.348764
iter 100 value 81.124584
final value 81.124584
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.230236
iter 10 value 94.951539
iter 20 value 89.529060
iter 30 value 88.267537
iter 40 value 85.159227
iter 50 value 84.364180
iter 60 value 84.035073
iter 70 value 82.491992
iter 80 value 82.209577
iter 90 value 81.978482
iter 100 value 81.127007
final value 81.127007
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 113.735582
iter 10 value 93.953539
iter 20 value 86.606732
iter 30 value 84.978758
iter 40 value 83.853832
iter 50 value 83.778013
iter 60 value 83.753850
iter 70 value 83.345561
iter 80 value 82.204499
iter 90 value 81.649882
iter 100 value 81.180610
final value 81.180610
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 102.545649
iter 10 value 94.076387
iter 20 value 89.553215
iter 30 value 87.110239
iter 40 value 84.460140
iter 50 value 82.966517
iter 60 value 81.432577
iter 70 value 81.326006
iter 80 value 80.827092
iter 90 value 80.419422
iter 100 value 80.304739
final value 80.304739
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.107554
iter 10 value 94.121141
iter 20 value 89.258012
iter 30 value 86.557113
iter 40 value 83.095539
iter 50 value 82.342987
iter 60 value 82.125699
iter 70 value 81.478602
iter 80 value 81.197347
iter 90 value 80.888089
iter 100 value 80.755361
final value 80.755361
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 104.814296
iter 10 value 94.645825
iter 20 value 94.066957
iter 30 value 87.633629
iter 40 value 84.192886
iter 50 value 83.257187
iter 60 value 82.270414
iter 70 value 81.808211
iter 80 value 81.053515
iter 90 value 80.557251
iter 100 value 80.301602
final value 80.301602
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 137.403340
iter 10 value 102.932386
iter 20 value 100.077476
iter 30 value 96.099065
iter 40 value 89.887329
iter 50 value 87.885263
iter 60 value 84.290335
iter 70 value 81.970722
iter 80 value 81.421190
iter 90 value 80.892554
iter 100 value 80.473887
final value 80.473887
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 107.983805
iter 10 value 94.063923
iter 20 value 93.971902
iter 30 value 93.950286
iter 40 value 89.625979
iter 50 value 88.467943
iter 60 value 86.421304
iter 70 value 83.632435
iter 80 value 83.319961
iter 90 value 83.176311
iter 100 value 81.830245
final value 81.830245
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 115.719198
iter 10 value 93.449497
iter 20 value 86.032967
iter 30 value 83.208833
iter 40 value 81.117795
iter 50 value 80.249898
iter 60 value 79.990476
iter 70 value 79.914873
iter 80 value 79.887527
iter 90 value 79.865477
iter 100 value 79.839881
final value 79.839881
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 100.347247
iter 10 value 90.858729
iter 20 value 85.867315
iter 30 value 85.821306
iter 40 value 85.820681
iter 50 value 85.820463
final value 85.820339
converged
Fitting Repeat 2
# weights: 103
initial value 94.195408
final value 94.054286
converged
Fitting Repeat 3
# weights: 103
initial value 95.276528
final value 93.871460
converged
Fitting Repeat 4
# weights: 103
initial value 98.119942
iter 10 value 94.054643
final value 94.052987
converged
Fitting Repeat 5
# weights: 103
initial value 96.764843
final value 94.054483
converged
Fitting Repeat 1
# weights: 305
initial value 95.822050
iter 10 value 94.060223
iter 20 value 93.936749
iter 30 value 93.879476
iter 40 value 89.188833
final value 87.796971
converged
Fitting Repeat 2
# weights: 305
initial value 101.928527
iter 10 value 94.101018
iter 20 value 90.180715
iter 30 value 86.229733
iter 40 value 86.221296
iter 50 value 86.219358
iter 60 value 85.488772
iter 70 value 85.033552
iter 80 value 85.029833
final value 85.029779
converged
Fitting Repeat 3
# weights: 305
initial value 97.322672
iter 10 value 94.055014
iter 20 value 92.262635
iter 30 value 92.252979
final value 92.252951
converged
Fitting Repeat 4
# weights: 305
initial value 107.957071
iter 10 value 94.057788
iter 20 value 94.052537
iter 30 value 88.200161
iter 40 value 87.118229
iter 50 value 84.533202
iter 60 value 84.282469
final value 84.282336
converged
Fitting Repeat 5
# weights: 305
initial value 96.867365
iter 10 value 93.909247
iter 20 value 83.545258
iter 30 value 80.707032
iter 40 value 79.807783
iter 50 value 79.792213
iter 60 value 79.789733
iter 70 value 79.761640
iter 80 value 79.689919
iter 90 value 79.399949
iter 100 value 79.188509
final value 79.188509
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 94.528658
iter 10 value 94.060861
iter 20 value 93.793280
iter 30 value 89.260970
iter 40 value 84.587436
iter 50 value 84.391943
iter 60 value 84.024322
iter 70 value 83.802916
iter 80 value 83.441874
iter 90 value 80.628457
iter 100 value 80.044547
final value 80.044547
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 96.243463
iter 10 value 93.924246
iter 20 value 93.916462
iter 30 value 88.781685
iter 40 value 85.828682
iter 50 value 85.816754
iter 60 value 85.792722
iter 70 value 84.654637
iter 80 value 84.602572
iter 90 value 84.582090
iter 100 value 84.450592
final value 84.450592
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 120.763084
iter 10 value 85.281761
iter 20 value 85.085794
iter 30 value 84.643973
iter 40 value 84.580984
iter 50 value 84.577233
iter 60 value 83.763799
iter 70 value 83.493076
final value 83.491316
converged
Fitting Repeat 4
# weights: 507
initial value 101.085554
iter 10 value 93.923673
iter 20 value 93.917161
iter 30 value 93.856759
iter 40 value 89.732504
iter 50 value 87.349886
iter 60 value 87.348171
iter 70 value 87.347363
iter 80 value 85.749071
iter 90 value 85.713046
final value 85.712150
converged
Fitting Repeat 5
# weights: 507
initial value 111.286036
iter 10 value 94.061363
iter 20 value 93.784387
iter 30 value 91.482223
iter 40 value 91.471144
iter 50 value 91.450054
iter 60 value 84.512905
iter 70 value 84.452300
iter 80 value 84.450729
final value 84.450556
converged
Fitting Repeat 1
# weights: 103
initial value 99.626269
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 98.773743
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 102.163111
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 97.269898
final value 94.443243
converged
Fitting Repeat 5
# weights: 103
initial value 96.280592
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 95.393350
iter 10 value 94.347952
iter 20 value 94.346670
final value 94.346669
converged
Fitting Repeat 2
# weights: 305
initial value 109.997706
final value 94.443243
converged
Fitting Repeat 3
# weights: 305
initial value 96.810303
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 95.287121
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 104.905683
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 96.206062
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 110.478165
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 99.104553
iter 10 value 94.443243
iter 10 value 94.443243
iter 10 value 94.443243
final value 94.443243
converged
Fitting Repeat 4
# weights: 507
initial value 118.293885
iter 10 value 93.682166
iter 20 value 91.890395
iter 30 value 91.861848
iter 30 value 91.861847
iter 30 value 91.861847
final value 91.861847
converged
Fitting Repeat 5
# weights: 507
initial value 112.875028
iter 10 value 93.750014
iter 20 value 93.672865
final value 93.672727
converged
Fitting Repeat 1
# weights: 103
initial value 102.174591
iter 10 value 94.390175
iter 20 value 93.928706
iter 30 value 93.857660
iter 40 value 90.480913
iter 50 value 89.307237
iter 60 value 87.282662
iter 70 value 86.703472
iter 80 value 86.390505
iter 90 value 86.339460
iter 100 value 86.326858
final value 86.326858
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 98.610693
iter 10 value 94.492115
iter 20 value 94.444892
iter 30 value 87.829352
iter 40 value 87.233613
iter 50 value 86.912016
iter 60 value 86.761749
iter 70 value 86.712575
iter 80 value 86.680023
final value 86.678090
converged
Fitting Repeat 3
# weights: 103
initial value 102.243629
iter 10 value 94.470886
iter 20 value 93.809539
iter 30 value 91.916365
iter 40 value 91.404031
iter 50 value 91.242224
iter 60 value 91.216104
iter 70 value 91.215827
iter 70 value 91.215826
iter 70 value 91.215826
final value 91.215826
converged
Fitting Repeat 4
# weights: 103
initial value 102.367242
iter 10 value 94.486601
iter 20 value 94.107668
iter 30 value 92.591786
iter 40 value 91.807990
iter 50 value 87.080962
iter 60 value 86.788265
iter 70 value 86.679483
iter 80 value 86.678102
final value 86.678092
converged
Fitting Repeat 5
# weights: 103
initial value 102.317051
iter 10 value 95.099977
iter 20 value 94.461819
iter 30 value 92.463453
iter 40 value 91.540485
iter 50 value 87.415640
iter 60 value 87.180334
iter 70 value 87.057240
iter 80 value 85.898971
iter 90 value 84.592713
iter 100 value 84.478057
final value 84.478057
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 114.165640
iter 10 value 94.289499
iter 20 value 90.857774
iter 30 value 87.156717
iter 40 value 86.159838
iter 50 value 84.621472
iter 60 value 84.311689
iter 70 value 83.812785
iter 80 value 83.620362
iter 90 value 83.495696
iter 100 value 83.483348
final value 83.483348
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.935986
iter 10 value 94.450514
iter 20 value 90.313316
iter 30 value 89.091882
iter 40 value 87.172858
iter 50 value 85.541415
iter 60 value 85.369014
iter 70 value 85.111897
iter 80 value 84.986701
iter 90 value 84.591584
iter 100 value 83.746462
final value 83.746462
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 104.252645
iter 10 value 93.996655
iter 20 value 89.706605
iter 30 value 86.980561
iter 40 value 85.183588
iter 50 value 84.608521
iter 60 value 84.303384
iter 70 value 84.147523
iter 80 value 83.701119
iter 90 value 83.438991
iter 100 value 83.395822
final value 83.395822
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 102.710776
iter 10 value 94.424243
iter 20 value 92.914590
iter 30 value 89.089168
iter 40 value 87.351540
iter 50 value 86.293624
iter 60 value 86.104241
iter 70 value 86.009081
iter 80 value 85.941782
iter 90 value 85.908899
iter 100 value 85.741326
final value 85.741326
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 118.298965
iter 10 value 94.518087
iter 20 value 92.991963
iter 30 value 89.455379
iter 40 value 87.368871
iter 50 value 85.598960
iter 60 value 84.517645
iter 70 value 84.380781
iter 80 value 84.001708
iter 90 value 83.701667
iter 100 value 83.415384
final value 83.415384
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.300453
iter 10 value 94.428968
iter 20 value 90.922019
iter 30 value 88.431698
iter 40 value 86.038781
iter 50 value 85.607589
iter 60 value 84.686135
iter 70 value 84.481857
iter 80 value 84.309462
iter 90 value 84.298111
iter 100 value 84.194285
final value 84.194285
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.785801
iter 10 value 95.025058
iter 20 value 89.368062
iter 30 value 88.885559
iter 40 value 88.575212
iter 50 value 86.674954
iter 60 value 84.859249
iter 70 value 84.429426
iter 80 value 84.043876
iter 90 value 83.718966
iter 100 value 83.695101
final value 83.695101
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.068194
iter 10 value 94.624578
iter 20 value 94.256552
iter 30 value 90.373267
iter 40 value 87.907935
iter 50 value 87.179838
iter 60 value 85.354487
iter 70 value 84.667282
iter 80 value 84.584081
iter 90 value 84.197503
iter 100 value 83.695767
final value 83.695767
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 106.847886
iter 10 value 94.226914
iter 20 value 91.372145
iter 30 value 87.148374
iter 40 value 86.401554
iter 50 value 84.669813
iter 60 value 84.042546
iter 70 value 83.582298
iter 80 value 83.412670
iter 90 value 83.376255
iter 100 value 83.276691
final value 83.276691
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 114.401873
iter 10 value 94.743618
iter 20 value 92.482552
iter 30 value 89.364582
iter 40 value 86.802036
iter 50 value 86.145763
iter 60 value 85.244394
iter 70 value 84.442058
iter 80 value 83.925726
iter 90 value 83.754662
iter 100 value 83.602005
final value 83.602005
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 104.373025
iter 10 value 94.485809
iter 20 value 94.484016
iter 30 value 92.655256
iter 40 value 88.658764
iter 50 value 88.304535
iter 60 value 88.203526
iter 70 value 87.999255
iter 80 value 87.837510
iter 80 value 87.837510
iter 80 value 87.837510
final value 87.837510
converged
Fitting Repeat 2
# weights: 103
initial value 102.549241
final value 94.485693
converged
Fitting Repeat 3
# weights: 103
initial value 102.484833
final value 94.485751
converged
Fitting Repeat 4
# weights: 103
initial value 96.854838
final value 94.485812
converged
Fitting Repeat 5
# weights: 103
initial value 96.621939
final value 94.485600
converged
Fitting Repeat 1
# weights: 305
initial value 106.142526
iter 10 value 94.488531
iter 20 value 94.452884
iter 30 value 92.174948
iter 40 value 92.108348
iter 50 value 90.980717
iter 60 value 90.819110
final value 90.783961
converged
Fitting Repeat 2
# weights: 305
initial value 117.343461
iter 10 value 94.489143
iter 20 value 94.351530
iter 30 value 87.294718
iter 40 value 86.842845
iter 50 value 86.841946
iter 60 value 86.826607
iter 70 value 86.700238
iter 80 value 86.341612
iter 90 value 83.926191
iter 100 value 83.466364
final value 83.466364
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 116.134191
iter 10 value 94.489254
iter 20 value 94.454662
iter 30 value 92.047760
iter 40 value 90.538148
iter 50 value 90.536875
final value 90.535716
converged
Fitting Repeat 4
# weights: 305
initial value 96.789107
iter 10 value 93.689225
iter 20 value 93.579627
iter 30 value 92.788746
iter 40 value 92.771217
iter 50 value 92.397803
iter 60 value 86.541261
final value 86.056148
converged
Fitting Repeat 5
# weights: 305
initial value 101.162156
iter 10 value 94.488758
iter 20 value 94.473650
iter 30 value 93.912383
iter 40 value 91.359944
iter 50 value 90.132130
iter 60 value 89.392322
iter 70 value 89.358252
iter 80 value 89.289115
final value 89.289054
converged
Fitting Repeat 1
# weights: 507
initial value 102.581824
iter 10 value 94.491953
iter 20 value 94.477431
iter 30 value 94.447829
iter 40 value 94.443390
iter 50 value 93.392728
iter 60 value 91.862410
iter 70 value 91.803017
iter 80 value 88.777496
iter 90 value 84.345138
iter 100 value 83.971407
final value 83.971407
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 116.719275
iter 10 value 94.451374
iter 20 value 94.444077
iter 30 value 92.826901
iter 40 value 90.728964
iter 50 value 85.509710
iter 60 value 84.255524
iter 70 value 83.427182
iter 80 value 82.990074
iter 90 value 82.988413
final value 82.988410
converged
Fitting Repeat 3
# weights: 507
initial value 95.811681
iter 10 value 89.816891
iter 20 value 87.236239
iter 30 value 84.654031
iter 40 value 84.386731
iter 50 value 84.307851
iter 60 value 84.303319
iter 70 value 84.117194
iter 80 value 83.592355
iter 90 value 83.262960
iter 100 value 83.256890
final value 83.256890
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 109.257250
iter 10 value 94.492730
iter 20 value 94.483286
iter 30 value 89.362907
iter 40 value 88.625823
iter 50 value 88.374412
iter 60 value 84.241809
iter 70 value 84.126982
iter 80 value 84.071153
iter 90 value 84.068924
iter 100 value 84.064545
final value 84.064545
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 95.263466
iter 10 value 94.346070
iter 20 value 94.342778
iter 30 value 94.316558
iter 40 value 94.307918
iter 50 value 94.307843
final value 94.307466
converged
Fitting Repeat 1
# weights: 305
initial value 124.735521
iter 10 value 117.782918
iter 20 value 111.312563
iter 30 value 105.601327
iter 40 value 102.092190
iter 50 value 101.309713
iter 60 value 101.067363
iter 70 value 100.839488
iter 80 value 100.725085
iter 90 value 100.611339
iter 100 value 100.592855
final value 100.592855
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 138.958791
iter 10 value 117.897852
iter 20 value 117.667995
iter 30 value 116.324043
iter 40 value 112.383480
iter 50 value 106.228063
iter 60 value 102.517600
iter 70 value 101.843749
iter 80 value 101.145067
iter 90 value 101.039465
iter 100 value 100.895773
final value 100.895773
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 133.224977
iter 10 value 117.920736
iter 20 value 111.933322
iter 30 value 108.215124
iter 40 value 107.691490
iter 50 value 106.924242
iter 60 value 105.725000
iter 70 value 103.291836
iter 80 value 102.671057
iter 90 value 102.331703
iter 100 value 101.391677
final value 101.391677
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 128.652352
iter 10 value 117.855084
iter 20 value 113.538240
iter 30 value 108.810361
iter 40 value 105.203052
iter 50 value 103.688156
iter 60 value 103.445238
iter 70 value 103.127103
iter 80 value 103.027769
iter 90 value 102.802990
iter 100 value 102.024612
final value 102.024612
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 128.069864
iter 10 value 117.768634
iter 20 value 114.522949
iter 30 value 111.139245
iter 40 value 108.473094
iter 50 value 106.529237
iter 60 value 103.261747
iter 70 value 103.181429
iter 80 value 101.934072
iter 90 value 101.590514
iter 100 value 101.057046
final value 101.057046
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 -- Fri Mar 21 02:37:05 2025
***********************************************
Number of test functions: 7
Number of errors: 0
Number of failures: 0
1 Test Suite :
HPiP RUnit Tests - 7 test functions, 0 errors, 0 failures
Number of test functions: 7
Number of errors: 0
Number of failures: 0
Warning messages:
1: `repeats` has no meaning for this resampling method.
2: executing %dopar% sequentially: no parallel backend registered
>
>
>
>
> proc.time()
user system elapsed
42.40 1.54 92.25
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 34.56 | 1.85 | 36.42 | |
| FreqInteractors | 0.25 | 0.04 | 0.31 | |
| calculateAAC | 0.05 | 0.02 | 0.06 | |
| calculateAutocor | 0.76 | 0.06 | 0.83 | |
| calculateCTDC | 0.09 | 0.00 | 0.10 | |
| calculateCTDD | 0.75 | 0.02 | 0.76 | |
| calculateCTDT | 0.36 | 0.03 | 0.39 | |
| calculateCTriad | 0.31 | 0.06 | 0.38 | |
| calculateDC | 0.08 | 0.02 | 0.09 | |
| calculateF | 0.36 | 0.00 | 0.36 | |
| calculateKSAAP | 0.13 | 0.01 | 0.14 | |
| calculateQD_Sm | 2.09 | 0.17 | 2.27 | |
| calculateTC | 1.84 | 0.16 | 2.00 | |
| calculateTC_Sm | 0.30 | 0.03 | 0.33 | |
| corr_plot | 34.47 | 1.85 | 36.37 | |
| enrichfindP | 0.75 | 0.09 | 13.77 | |
| enrichfind_hp | 0.11 | 0.01 | 1.08 | |
| enrichplot | 0.42 | 0.04 | 0.45 | |
| filter_missing_values | 0 | 0 | 0 | |
| getFASTA | 0.02 | 0.01 | 2.30 | |
| getHPI | 0 | 0 | 0 | |
| get_negativePPI | 0 | 0 | 0 | |
| get_positivePPI | 0 | 0 | 0 | |
| impute_missing_data | 0 | 0 | 0 | |
| plotPPI | 0.10 | 0.00 | 0.09 | |
| pred_ensembel | 14.21 | 0.42 | 13.05 | |
| var_imp | 35.16 | 1.46 | 36.61 | |