| Back to Multiple platform build/check report for BioC 3.23: simplified long |
|
This page was generated on 2026-03-09 11:33 -0400 (Mon, 09 Mar 2026).
| Hostname | OS | Arch (*) | R version | Installed pkgs |
|---|---|---|---|---|
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) | x86_64 | R Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences" | 4508 |
| kjohnson3 | macOS 13.7.7 Ventura | arm64 | R Under development (unstable) (2026-02-28 r89501) -- "Unsuffered Consequences" | 3381 |
| 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 1009/2360 | Hostname | OS / Arch | INSTALL | BUILD | CHECK | BUILD BIN | ||||||||
| HPiP 1.17.2 (landing page) Matineh Rahmatbakhsh
| nebbiolo1 | Linux (Ubuntu 24.04.3 LTS) / x86_64 | OK | OK | OK | |||||||||
| kjohnson3 | macOS 13.7.7 Ventura / arm64 | ERROR | ERROR | skipped | skipped | |||||||||
| See other builds for HPiP in R Universe. | ||||||||||||||
|
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: 1.17.2 |
| Command: /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.2.tar.gz |
| StartedAt: 2026-03-09 00:09:18 -0400 (Mon, 09 Mar 2026) |
| EndedAt: 2026-03-09 00:24:28 -0400 (Mon, 09 Mar 2026) |
| EllapsedTime: 910.4 seconds |
| RetCode: 0 |
| Status: OK |
| CheckDir: HPiP.Rcheck |
| Warnings: 0 |
##############################################################################
##############################################################################
###
### Running command:
###
### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD check --install=check:HPiP.install-out.txt --library=/home/biocbuild/bbs-3.23-bioc/R/site-library --timings HPiP_1.17.2.tar.gz
###
##############################################################################
##############################################################################
* using log directory ‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck’
* using R Under development (unstable) (2026-03-05 r89546)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
GNU Fortran (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
* running under: Ubuntu 24.04.4 LTS
* using session charset: UTF-8
* current time: 2026-03-09 04:09:18 UTC
* checking for file ‘HPiP/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘HPiP’ version ‘1.17.2’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘HPiP’ can be installed ... OK
* checking installed package size ... OK
* checking package directory ... OK
* checking ‘build’ directory ... OK
* checking DESCRIPTION meta-information ... NOTE
License stub is invalid DCF.
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... OK
* checking Rd files ... NOTE
checkRd: (-1) getHPI.Rd:29: Lost braces
29 | then the Kronecker product is the code{(pm × qn)} block matrix
| ^
* checking Rd metadata ... OK
* checking Rd cross-references ... INFO
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 34.879 0.521 35.433
corr_plot 33.620 0.389 34.009
FSmethod 32.413 0.586 33.001
pred_ensembel 12.496 0.108 11.317
enrichfindP 0.503 0.039 15.619
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
Running ‘runTests.R’
OK
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes ... OK
* checking re-building of vignette outputs ... OK
* checking PDF version of manual ... OK
* DONE
Status: 2 NOTEs
See
‘/home/biocbuild/bbs-3.23-bioc/meat/HPiP.Rcheck/00check.log’
for details.
HPiP.Rcheck/00install.out
############################################################################## ############################################################################## ### ### Running command: ### ### /home/biocbuild/bbs-3.23-bioc/R/bin/R CMD INSTALL HPiP ### ############################################################################## ############################################################################## * installing to library ‘/home/biocbuild/bbs-3.23-bioc/R/site-library’ * installing *source* package ‘HPiP’ ... ** this is package ‘HPiP’ version ‘1.17.2’ ** 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 Under development (unstable) (2026-03-05 r89546) -- "Unsuffered Consequences"
Copyright (C) 2026 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> BiocGenerics:::testPackage('HPiP')
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
No results to show
Please make sure that the organism is correct or set significant = FALSE
avNNet
Loading required package: ggplot2
Loading required package: lattice
Fitting Repeat 1
# weights: 103
initial value 100.426848
iter 10 value 91.971370
iter 20 value 87.374758
iter 30 value 87.040638
iter 40 value 87.031250
iter 40 value 87.031250
final value 87.031250
converged
Fitting Repeat 2
# weights: 103
initial value 100.320013
final value 93.903984
converged
Fitting Repeat 3
# weights: 103
initial value 99.405009
final value 93.903984
converged
Fitting Repeat 4
# weights: 103
initial value 97.229611
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 106.559581
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 106.193386
final value 93.582418
converged
Fitting Repeat 2
# weights: 305
initial value 106.421712
final value 94.052910
converged
Fitting Repeat 3
# weights: 305
initial value 103.449955
final value 94.052910
converged
Fitting Repeat 4
# weights: 305
initial value 106.598195
final value 93.582418
converged
Fitting Repeat 5
# weights: 305
initial value 96.557521
iter 10 value 93.582758
final value 93.582418
converged
Fitting Repeat 1
# weights: 507
initial value 114.773859
final value 94.052910
converged
Fitting Repeat 2
# weights: 507
initial value 117.226008
iter 10 value 90.872530
iter 20 value 90.414200
final value 90.414168
converged
Fitting Repeat 3
# weights: 507
initial value 94.443871
final value 94.052910
converged
Fitting Repeat 4
# weights: 507
initial value 105.391658
iter 10 value 93.826166
iter 20 value 93.341190
iter 30 value 93.067720
iter 40 value 93.062184
final value 93.062109
converged
Fitting Repeat 5
# weights: 507
initial value 111.382911
iter 10 value 92.754319
iter 20 value 91.371679
iter 30 value 91.350981
iter 40 value 91.082082
iter 50 value 90.587659
iter 60 value 90.138974
final value 90.138099
converged
Fitting Repeat 1
# weights: 103
initial value 101.379108
iter 10 value 94.009498
iter 20 value 93.434207
iter 30 value 88.911148
iter 40 value 84.643684
iter 50 value 83.981393
iter 60 value 83.602649
iter 70 value 83.489977
iter 80 value 82.945277
iter 90 value 82.169641
iter 100 value 81.868270
final value 81.868270
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 98.557530
iter 10 value 93.938196
iter 20 value 90.535192
iter 30 value 87.135072
iter 40 value 85.205775
iter 50 value 84.213031
iter 60 value 83.686344
iter 70 value 82.990325
iter 80 value 82.127684
iter 90 value 81.872479
iter 100 value 81.865375
final value 81.865375
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 103.342461
iter 10 value 94.054951
iter 20 value 93.420454
iter 30 value 93.322527
iter 40 value 91.992460
iter 50 value 86.044978
iter 60 value 84.537870
iter 70 value 83.561028
iter 80 value 83.345908
iter 90 value 83.319935
iter 100 value 83.318426
final value 83.318426
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 99.316895
iter 10 value 92.385401
iter 20 value 87.685509
iter 30 value 83.303869
iter 40 value 82.546362
iter 50 value 82.302179
iter 60 value 82.152245
iter 70 value 81.724070
iter 80 value 81.689168
iter 90 value 81.650278
final value 81.650198
converged
Fitting Repeat 5
# weights: 103
initial value 119.009461
iter 10 value 94.015100
iter 20 value 86.095286
iter 30 value 84.639957
iter 40 value 83.795320
iter 50 value 83.456658
iter 60 value 82.843003
iter 70 value 82.111563
iter 80 value 81.862666
iter 90 value 81.707676
iter 100 value 81.654446
final value 81.654446
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 114.518414
iter 10 value 94.885040
iter 20 value 93.082471
iter 30 value 89.159601
iter 40 value 86.261275
iter 50 value 82.936758
iter 60 value 81.629969
iter 70 value 81.327784
iter 80 value 81.186884
iter 90 value 81.055572
iter 100 value 81.002254
final value 81.002254
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 104.762868
iter 10 value 93.964589
iter 20 value 86.125851
iter 30 value 83.729637
iter 40 value 81.897563
iter 50 value 81.425678
iter 60 value 81.206668
iter 70 value 80.874135
iter 80 value 80.607393
iter 90 value 80.491813
iter 100 value 80.389907
final value 80.389907
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 117.903510
iter 10 value 94.270881
iter 20 value 93.553552
iter 30 value 90.641959
iter 40 value 84.125039
iter 50 value 83.655445
iter 60 value 82.828650
iter 70 value 81.848095
iter 80 value 81.510723
iter 90 value 81.455400
iter 100 value 81.428785
final value 81.428785
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 115.707058
iter 10 value 93.998647
iter 20 value 90.007702
iter 30 value 87.174429
iter 40 value 84.307019
iter 50 value 83.315578
iter 60 value 82.450835
iter 70 value 82.110443
iter 80 value 81.952648
iter 90 value 81.751433
iter 100 value 81.477884
final value 81.477884
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 106.577810
iter 10 value 93.995020
iter 20 value 93.688712
iter 30 value 93.154213
iter 40 value 90.040913
iter 50 value 88.646213
iter 60 value 86.062597
iter 70 value 85.181303
iter 80 value 84.437576
iter 90 value 84.107133
iter 100 value 83.584397
final value 83.584397
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 131.703194
iter 10 value 94.594706
iter 20 value 93.994878
iter 30 value 91.470283
iter 40 value 85.562744
iter 50 value 83.701533
iter 60 value 83.174868
iter 70 value 82.525011
iter 80 value 81.062341
iter 90 value 80.874543
iter 100 value 80.741304
final value 80.741304
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 107.289536
iter 10 value 94.146390
iter 20 value 89.661522
iter 30 value 85.992388
iter 40 value 82.526456
iter 50 value 81.225558
iter 60 value 81.008021
iter 70 value 80.675429
iter 80 value 80.534367
iter 90 value 80.381985
iter 100 value 80.171526
final value 80.171526
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 125.411132
iter 10 value 93.901106
iter 20 value 90.068164
iter 30 value 88.166013
iter 40 value 87.673422
iter 50 value 87.128896
iter 60 value 83.467817
iter 70 value 82.227996
iter 80 value 81.925338
iter 90 value 80.870875
iter 100 value 80.478985
final value 80.478985
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 104.131438
iter 10 value 94.519738
iter 20 value 86.765740
iter 30 value 85.455676
iter 40 value 82.070846
iter 50 value 80.988162
iter 60 value 80.641031
iter 70 value 80.409726
iter 80 value 80.280287
iter 90 value 80.250459
iter 100 value 80.226912
final value 80.226912
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 112.090138
iter 10 value 93.633939
iter 20 value 87.288939
iter 30 value 84.487153
iter 40 value 82.589261
iter 50 value 82.358504
iter 60 value 81.745641
iter 70 value 80.924001
iter 80 value 80.679357
iter 90 value 80.449820
iter 100 value 80.178949
final value 80.178949
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.531975
iter 10 value 93.905900
iter 20 value 93.819414
iter 30 value 92.319260
iter 40 value 92.286768
iter 50 value 92.285707
final value 92.285491
converged
Fitting Repeat 2
# weights: 103
initial value 95.875808
final value 94.054591
converged
Fitting Repeat 3
# weights: 103
initial value 102.818757
final value 94.054352
converged
Fitting Repeat 4
# weights: 103
initial value 99.936648
iter 10 value 94.054789
iter 20 value 94.052926
final value 94.052916
converged
Fitting Repeat 5
# weights: 103
initial value 94.995805
final value 94.054692
converged
Fitting Repeat 1
# weights: 305
initial value 94.559304
iter 10 value 84.913439
iter 20 value 83.555405
iter 30 value 83.553504
final value 83.549462
converged
Fitting Repeat 2
# weights: 305
initial value 111.904136
iter 10 value 94.057421
iter 20 value 93.840087
iter 30 value 87.238601
iter 40 value 85.050363
iter 50 value 85.022731
iter 60 value 85.017488
iter 70 value 84.805700
final value 84.805614
converged
Fitting Repeat 3
# weights: 305
initial value 104.019416
iter 10 value 94.111945
iter 20 value 94.025511
iter 30 value 91.721771
iter 40 value 91.660441
iter 50 value 91.628188
iter 60 value 89.797982
iter 70 value 89.597855
iter 80 value 89.379936
iter 90 value 85.311548
iter 100 value 85.310669
final value 85.310669
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 96.660123
iter 10 value 94.053970
iter 20 value 93.975430
iter 30 value 86.340941
iter 40 value 85.486147
iter 50 value 85.441391
iter 60 value 85.440981
iter 70 value 85.375879
iter 80 value 85.238992
iter 80 value 85.238991
iter 80 value 85.238991
final value 85.238991
converged
Fitting Repeat 5
# weights: 305
initial value 110.087268
final value 94.057531
converged
Fitting Repeat 1
# weights: 507
initial value 123.751709
iter 10 value 93.590387
iter 20 value 93.583540
iter 30 value 88.335004
iter 40 value 83.895808
iter 50 value 83.802025
iter 60 value 83.649027
iter 70 value 82.942310
iter 80 value 82.800545
final value 82.800342
converged
Fitting Repeat 2
# weights: 507
initial value 98.768861
iter 10 value 94.060707
iter 20 value 94.053036
iter 30 value 94.039466
iter 40 value 88.197910
iter 50 value 83.487026
iter 60 value 82.876666
iter 70 value 81.347101
iter 80 value 80.360008
iter 90 value 80.242902
iter 100 value 80.240988
final value 80.240988
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 103.772768
iter 10 value 93.382043
iter 20 value 92.954244
iter 30 value 92.804809
iter 40 value 92.716728
iter 50 value 92.713539
iter 60 value 92.048638
iter 70 value 91.913524
iter 80 value 90.071490
iter 90 value 81.980994
iter 100 value 80.436952
final value 80.436952
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 96.810833
iter 10 value 93.590676
iter 20 value 93.314087
iter 30 value 92.816349
iter 40 value 87.884470
iter 50 value 83.263053
iter 60 value 83.256049
iter 70 value 83.255289
iter 80 value 83.179048
iter 90 value 83.157789
iter 90 value 83.157789
iter 90 value 83.157789
final value 83.157789
converged
Fitting Repeat 5
# weights: 507
initial value 98.177001
iter 10 value 93.589296
iter 20 value 93.580006
iter 30 value 92.861969
iter 40 value 89.875788
iter 50 value 84.539409
iter 60 value 84.538955
iter 70 value 84.538587
iter 80 value 83.364442
iter 90 value 83.121867
iter 100 value 81.808043
final value 81.808043
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 98.445069
final value 94.473119
converged
Fitting Repeat 2
# weights: 103
initial value 101.969525
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 107.155757
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 95.045968
final value 93.701657
converged
Fitting Repeat 5
# weights: 103
initial value 98.200523
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 94.400627
iter 10 value 87.172003
iter 20 value 86.782114
final value 86.782049
converged
Fitting Repeat 2
# weights: 305
initial value 116.955644
final value 93.837462
converged
Fitting Repeat 3
# weights: 305
initial value 98.995520
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 99.448498
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 105.094235
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 97.000886
iter 10 value 93.217715
iter 20 value 93.092585
iter 30 value 93.088117
final value 93.088098
converged
Fitting Repeat 2
# weights: 507
initial value 106.120433
final value 94.473118
converged
Fitting Repeat 3
# weights: 507
initial value 95.939982
final value 94.484211
converged
Fitting Repeat 4
# weights: 507
initial value 116.074474
iter 10 value 94.892842
final value 94.473118
converged
Fitting Repeat 5
# weights: 507
initial value 97.745654
iter 10 value 88.597732
iter 20 value 88.165588
iter 30 value 88.155194
final value 88.155167
converged
Fitting Repeat 1
# weights: 103
initial value 100.679449
iter 10 value 92.429490
iter 20 value 88.033794
iter 30 value 85.995801
iter 40 value 85.755678
iter 50 value 85.552831
iter 60 value 85.187947
iter 70 value 84.981307
final value 84.978372
converged
Fitting Repeat 2
# weights: 103
initial value 104.782203
iter 10 value 94.488589
iter 20 value 93.966799
iter 30 value 91.932300
iter 40 value 86.878373
iter 50 value 86.042023
iter 60 value 85.278045
iter 70 value 85.006482
iter 80 value 84.972036
final value 84.971997
converged
Fitting Repeat 3
# weights: 103
initial value 109.530657
iter 10 value 94.434858
iter 20 value 87.173638
iter 30 value 85.614264
iter 40 value 83.048958
iter 50 value 82.280545
iter 60 value 81.605818
iter 70 value 81.165010
iter 80 value 81.126881
final value 81.126879
converged
Fitting Repeat 4
# weights: 103
initial value 104.401503
iter 10 value 94.520549
iter 20 value 94.481099
iter 30 value 93.564242
iter 40 value 91.564293
iter 50 value 83.328736
iter 60 value 82.225295
iter 70 value 81.910403
iter 80 value 81.715198
iter 90 value 81.379122
iter 100 value 81.296944
final value 81.296944
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 103.762657
iter 10 value 94.626319
iter 20 value 94.112619
iter 30 value 91.209756
iter 40 value 88.775245
iter 50 value 87.321694
iter 60 value 85.821393
iter 70 value 85.107274
iter 80 value 84.972734
iter 90 value 84.971997
iter 90 value 84.971997
iter 90 value 84.971997
final value 84.971997
converged
Fitting Repeat 1
# weights: 305
initial value 102.622295
iter 10 value 94.448531
iter 20 value 93.102195
iter 30 value 86.729611
iter 40 value 84.761018
iter 50 value 84.094970
iter 60 value 83.471815
iter 70 value 81.555267
iter 80 value 80.743254
iter 90 value 80.219827
iter 100 value 80.069890
final value 80.069890
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 107.286547
iter 10 value 94.664476
iter 20 value 94.488523
iter 30 value 93.771499
iter 40 value 89.731885
iter 50 value 85.747135
iter 60 value 83.416680
iter 70 value 81.740474
iter 80 value 80.820540
iter 90 value 80.678041
iter 100 value 80.380702
final value 80.380702
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 100.803000
iter 10 value 94.489680
iter 20 value 94.488094
iter 30 value 93.842815
iter 40 value 89.642966
iter 50 value 87.226573
iter 60 value 84.964678
iter 70 value 82.966736
iter 80 value 82.504959
iter 90 value 81.388045
iter 100 value 80.975316
final value 80.975316
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 126.396727
iter 10 value 96.232146
iter 20 value 86.342485
iter 30 value 85.699323
iter 40 value 85.439469
iter 50 value 85.332895
iter 60 value 85.314552
iter 70 value 85.240339
iter 80 value 85.043162
iter 90 value 83.899538
iter 100 value 82.713658
final value 82.713658
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 124.920654
iter 10 value 94.395930
iter 20 value 92.125014
iter 30 value 87.723870
iter 40 value 84.016548
iter 50 value 82.955501
iter 60 value 82.645747
iter 70 value 82.394597
iter 80 value 82.232937
iter 90 value 81.953867
iter 100 value 81.068025
final value 81.068025
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 111.762946
iter 10 value 94.535162
iter 20 value 92.665507
iter 30 value 89.154331
iter 40 value 84.056926
iter 50 value 82.446812
iter 60 value 81.544595
iter 70 value 81.240004
iter 80 value 81.073490
iter 90 value 80.540605
iter 100 value 80.162270
final value 80.162270
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.174601
iter 10 value 95.707061
iter 20 value 88.143580
iter 30 value 86.210529
iter 40 value 84.885425
iter 50 value 82.809504
iter 60 value 82.188486
iter 70 value 81.314220
iter 80 value 80.575459
iter 90 value 80.423064
iter 100 value 80.114699
final value 80.114699
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.616294
iter 10 value 96.647660
iter 20 value 88.389509
iter 30 value 83.353475
iter 40 value 81.566011
iter 50 value 81.261224
iter 60 value 80.004594
iter 70 value 79.578388
iter 80 value 79.418113
iter 90 value 79.378091
iter 100 value 79.359892
final value 79.359892
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 118.562957
iter 10 value 99.055661
iter 20 value 90.602373
iter 30 value 86.162251
iter 40 value 83.996075
iter 50 value 83.247467
iter 60 value 82.328483
iter 70 value 81.566655
iter 80 value 81.213473
iter 90 value 80.857539
iter 100 value 80.647308
final value 80.647308
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 125.956561
iter 10 value 94.795608
iter 20 value 93.671497
iter 30 value 89.390387
iter 40 value 87.056053
iter 50 value 85.677271
iter 60 value 85.143465
iter 70 value 84.997665
iter 80 value 83.715529
iter 90 value 83.299110
iter 100 value 82.648433
final value 82.648433
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.705671
final value 94.485849
converged
Fitting Repeat 2
# weights: 103
initial value 95.289183
final value 94.485746
converged
Fitting Repeat 3
# weights: 103
initial value 96.713926
iter 10 value 94.474606
iter 20 value 94.472155
iter 30 value 90.149469
iter 40 value 88.290186
iter 50 value 88.283917
iter 60 value 88.280861
iter 70 value 87.195711
final value 86.160114
converged
Fitting Repeat 4
# weights: 103
initial value 95.404970
final value 94.485996
converged
Fitting Repeat 5
# weights: 103
initial value 105.558727
final value 94.485860
converged
Fitting Repeat 1
# weights: 305
initial value 107.036545
iter 10 value 94.478283
iter 20 value 94.091203
iter 30 value 93.842401
iter 40 value 92.115149
iter 50 value 85.314877
iter 60 value 84.243183
iter 70 value 82.281163
iter 80 value 81.938650
iter 90 value 81.932755
iter 100 value 81.385279
final value 81.385279
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 96.826113
iter 10 value 93.706578
iter 20 value 93.551309
iter 30 value 92.741723
iter 40 value 88.778107
iter 50 value 88.768413
iter 60 value 88.596673
iter 70 value 88.590076
iter 80 value 88.589201
iter 90 value 88.588045
iter 100 value 88.573270
final value 88.573270
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 102.502424
iter 10 value 94.478120
iter 20 value 94.451069
iter 30 value 92.516990
iter 40 value 92.421805
iter 50 value 91.391519
final value 91.311316
converged
Fitting Repeat 4
# weights: 305
initial value 109.489909
iter 10 value 94.491288
iter 20 value 94.391889
iter 30 value 93.454347
final value 92.856375
converged
Fitting Repeat 5
# weights: 305
initial value 101.536870
iter 10 value 94.489119
iter 20 value 94.405588
iter 30 value 85.597559
iter 40 value 84.832082
iter 50 value 84.806094
iter 60 value 84.802871
iter 70 value 84.802669
iter 80 value 84.519691
iter 90 value 84.195973
final value 84.187105
converged
Fitting Repeat 1
# weights: 507
initial value 106.639471
iter 10 value 94.446047
iter 20 value 94.354071
iter 30 value 94.347591
iter 40 value 94.152062
iter 50 value 86.435721
iter 60 value 84.236467
iter 70 value 83.307269
iter 80 value 83.083678
iter 90 value 83.074847
iter 100 value 82.865868
final value 82.865868
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 106.331714
iter 10 value 94.492057
iter 20 value 94.469521
iter 30 value 87.099198
final value 87.099196
converged
Fitting Repeat 3
# weights: 507
initial value 105.069022
iter 10 value 94.481262
iter 20 value 94.442027
iter 30 value 84.691279
iter 40 value 84.473140
iter 50 value 82.313808
iter 60 value 82.296199
iter 70 value 82.219680
final value 82.207996
converged
Fitting Repeat 4
# weights: 507
initial value 126.687227
iter 10 value 94.492889
iter 20 value 94.484742
iter 30 value 94.439056
iter 40 value 90.835855
iter 50 value 89.444646
iter 60 value 87.338933
iter 70 value 87.289777
iter 80 value 86.234692
iter 90 value 86.159245
iter 100 value 86.158871
final value 86.158871
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 99.737737
iter 10 value 93.712796
iter 20 value 93.710283
iter 30 value 93.707801
iter 40 value 93.686554
iter 50 value 90.814250
iter 60 value 86.730940
iter 70 value 86.727351
iter 80 value 86.723469
iter 90 value 86.699514
iter 100 value 86.465201
final value 86.465201
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 99.442483
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 95.292567
final value 94.484211
converged
Fitting Repeat 3
# weights: 103
initial value 100.676546
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 99.631750
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 95.258088
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 118.258938
final value 94.484211
converged
Fitting Repeat 2
# weights: 305
initial value 97.004909
iter 10 value 93.809365
final value 93.794996
converged
Fitting Repeat 3
# weights: 305
initial value 106.873278
final value 94.484211
converged
Fitting Repeat 4
# weights: 305
initial value 115.123196
final value 94.484211
converged
Fitting Repeat 5
# weights: 305
initial value 118.877915
final value 94.026542
converged
Fitting Repeat 1
# weights: 507
initial value 96.746539
final value 94.484211
converged
Fitting Repeat 2
# weights: 507
initial value 107.192702
final value 94.484211
converged
Fitting Repeat 3
# weights: 507
initial value 96.017584
iter 10 value 94.230452
final value 94.229692
converged
Fitting Repeat 4
# weights: 507
initial value 98.047294
final value 94.026542
converged
Fitting Repeat 5
# weights: 507
initial value 120.725646
final value 94.305882
converged
Fitting Repeat 1
# weights: 103
initial value 100.755385
iter 10 value 94.409536
iter 20 value 94.134918
iter 30 value 93.946104
iter 40 value 84.963378
iter 50 value 84.093858
iter 60 value 83.348720
iter 70 value 81.052369
iter 80 value 80.436909
final value 80.436508
converged
Fitting Repeat 2
# weights: 103
initial value 100.681729
iter 10 value 94.130770
iter 20 value 92.949946
iter 30 value 90.500322
iter 40 value 89.694400
iter 50 value 88.016724
iter 60 value 86.849947
iter 70 value 83.992138
iter 80 value 82.527131
iter 90 value 81.878302
iter 100 value 81.328420
final value 81.328420
stopped after 100 iterations
Fitting Repeat 3
# weights: 103
initial value 101.718431
iter 10 value 94.489241
iter 20 value 93.303949
iter 30 value 86.289157
iter 40 value 85.874167
iter 50 value 82.255813
iter 60 value 81.055784
iter 70 value 80.704201
iter 80 value 80.475551
iter 90 value 80.436509
iter 90 value 80.436509
iter 90 value 80.436509
final value 80.436509
converged
Fitting Repeat 4
# weights: 103
initial value 99.337813
iter 10 value 94.488418
iter 20 value 94.031711
iter 30 value 93.508841
iter 40 value 90.693283
iter 50 value 90.247801
iter 60 value 90.196819
iter 70 value 87.271498
iter 80 value 83.236838
iter 90 value 81.396005
iter 100 value 81.225367
final value 81.225367
stopped after 100 iterations
Fitting Repeat 5
# weights: 103
initial value 103.677640
iter 10 value 94.463711
iter 20 value 94.216757
iter 30 value 93.764474
iter 40 value 87.268192
iter 50 value 84.813279
iter 60 value 82.361007
iter 70 value 81.880788
iter 80 value 81.075652
iter 90 value 81.061973
iter 100 value 81.060069
final value 81.060069
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 103.034674
iter 10 value 90.744962
iter 20 value 84.538788
iter 30 value 84.053615
iter 40 value 83.648400
iter 50 value 81.281934
iter 60 value 80.478004
iter 70 value 80.177301
iter 80 value 79.776387
iter 90 value 79.520473
iter 100 value 79.482264
final value 79.482264
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 112.823939
iter 10 value 94.492937
iter 20 value 94.010818
iter 30 value 85.716437
iter 40 value 83.725694
iter 50 value 82.680893
iter 60 value 81.827045
iter 70 value 81.080509
iter 80 value 80.763973
iter 90 value 80.492797
iter 100 value 80.423121
final value 80.423121
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 101.096998
iter 10 value 94.388805
iter 20 value 90.752066
iter 30 value 86.558689
iter 40 value 84.649420
iter 50 value 83.033913
iter 60 value 82.133301
iter 70 value 80.845611
iter 80 value 79.818743
iter 90 value 79.310847
iter 100 value 78.839698
final value 78.839698
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 114.665121
iter 10 value 94.538607
iter 20 value 94.310727
iter 30 value 85.504297
iter 40 value 84.609507
iter 50 value 82.663641
iter 60 value 82.053076
iter 70 value 81.884356
iter 80 value 80.121473
iter 90 value 79.728294
iter 100 value 79.241451
final value 79.241451
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.033893
iter 10 value 93.906168
iter 20 value 91.792187
iter 30 value 83.683263
iter 40 value 83.348938
iter 50 value 82.250143
iter 60 value 81.974659
iter 70 value 81.450013
iter 80 value 80.987394
iter 90 value 79.778692
iter 100 value 79.423129
final value 79.423129
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 104.130012
iter 10 value 86.658897
iter 20 value 84.204296
iter 30 value 83.001095
iter 40 value 80.824795
iter 50 value 80.503540
iter 60 value 79.572546
iter 70 value 79.377436
iter 80 value 79.340280
iter 90 value 79.288353
iter 100 value 79.185441
final value 79.185441
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.410172
iter 10 value 94.491754
iter 20 value 93.358526
iter 30 value 87.249950
iter 40 value 86.422857
iter 50 value 86.065061
iter 60 value 83.765433
iter 70 value 82.883744
iter 80 value 81.656502
iter 90 value 80.052003
iter 100 value 79.294338
final value 79.294338
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 104.999551
iter 10 value 94.143286
iter 20 value 89.164650
iter 30 value 84.327732
iter 40 value 83.908368
iter 50 value 82.320045
iter 60 value 80.465587
iter 70 value 78.972557
iter 80 value 78.744616
iter 90 value 78.655212
iter 100 value 78.581249
final value 78.581249
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 131.752180
iter 10 value 95.240043
iter 20 value 89.908638
iter 30 value 85.800100
iter 40 value 82.968077
iter 50 value 81.210053
iter 60 value 80.438437
iter 70 value 79.975415
iter 80 value 79.727303
iter 90 value 79.300337
iter 100 value 79.056967
final value 79.056967
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 113.478375
iter 10 value 93.881022
iter 20 value 90.251506
iter 30 value 88.275952
iter 40 value 85.033609
iter 50 value 81.520951
iter 60 value 80.643827
iter 70 value 80.258889
iter 80 value 79.880124
iter 90 value 79.540148
iter 100 value 79.035846
final value 79.035846
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 103.831052
final value 94.485817
converged
Fitting Repeat 2
# weights: 103
initial value 109.333277
final value 94.485834
converged
Fitting Repeat 3
# weights: 103
initial value 96.657356
final value 94.485871
converged
Fitting Repeat 4
# weights: 103
initial value 104.282278
final value 94.485676
converged
Fitting Repeat 5
# weights: 103
initial value 95.391774
final value 94.485680
converged
Fitting Repeat 1
# weights: 305
initial value 115.530103
iter 10 value 94.488757
iter 20 value 94.473025
iter 30 value 92.633108
iter 40 value 85.173935
final value 85.173860
converged
Fitting Repeat 2
# weights: 305
initial value 112.901171
iter 10 value 94.488901
iter 20 value 94.474717
iter 30 value 94.090480
iter 40 value 93.393201
iter 50 value 86.857215
final value 86.850155
converged
Fitting Repeat 3
# weights: 305
initial value 98.024331
iter 10 value 94.488622
iter 20 value 94.350158
iter 30 value 85.534739
final value 85.534478
converged
Fitting Repeat 4
# weights: 305
initial value 104.572517
iter 10 value 93.981995
iter 20 value 93.979554
final value 93.975959
converged
Fitting Repeat 5
# weights: 305
initial value 97.764820
iter 10 value 94.488913
iter 20 value 93.911101
iter 30 value 86.071126
iter 40 value 84.303211
iter 50 value 83.570278
iter 60 value 83.548067
iter 70 value 83.547545
iter 80 value 83.469546
iter 90 value 82.593566
iter 100 value 81.247613
final value 81.247613
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 107.958670
iter 10 value 94.493469
iter 20 value 94.486268
iter 30 value 93.646291
iter 40 value 93.616670
iter 50 value 93.598883
iter 60 value 93.339392
iter 70 value 93.257950
iter 80 value 91.332459
iter 90 value 84.130581
iter 100 value 82.959667
final value 82.959667
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 105.737749
iter 10 value 94.456368
iter 20 value 94.448992
final value 94.448885
converged
Fitting Repeat 3
# weights: 507
initial value 94.883036
iter 10 value 93.713481
iter 20 value 93.009994
iter 30 value 93.008020
iter 40 value 93.003583
iter 50 value 90.660602
iter 60 value 90.150729
iter 70 value 90.137142
iter 80 value 90.135061
iter 90 value 89.868211
iter 100 value 89.356990
final value 89.356990
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 108.589272
iter 10 value 91.153013
iter 20 value 83.049805
iter 30 value 83.034683
iter 40 value 82.179558
iter 50 value 81.962963
iter 60 value 81.945726
iter 70 value 81.924999
iter 80 value 81.492753
iter 90 value 78.982585
iter 100 value 78.569276
final value 78.569276
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.601466
iter 10 value 93.806613
iter 20 value 93.439773
iter 30 value 93.435554
iter 40 value 93.420391
iter 50 value 93.418148
iter 60 value 93.416836
iter 70 value 93.416678
final value 93.416658
converged
Fitting Repeat 1
# weights: 103
initial value 100.337987
iter 10 value 94.003413
iter 20 value 93.654219
final value 93.653871
converged
Fitting Repeat 2
# weights: 103
initial value 116.444118
final value 94.052910
converged
Fitting Repeat 3
# weights: 103
initial value 100.240845
final value 94.052910
converged
Fitting Repeat 4
# weights: 103
initial value 95.725340
final value 94.052910
converged
Fitting Repeat 5
# weights: 103
initial value 94.727499
final value 94.052910
converged
Fitting Repeat 1
# weights: 305
initial value 96.623117
final value 94.038251
converged
Fitting Repeat 2
# weights: 305
initial value 95.024482
final value 93.653870
converged
Fitting Repeat 3
# weights: 305
initial value 106.122504
iter 10 value 93.973339
iter 20 value 93.196443
iter 30 value 92.933117
final value 92.864740
converged
Fitting Repeat 4
# weights: 305
initial value 111.616144
final value 94.038251
converged
Fitting Repeat 5
# weights: 305
initial value 101.044035
final value 94.052910
converged
Fitting Repeat 1
# weights: 507
initial value 109.224692
final value 94.038251
converged
Fitting Repeat 2
# weights: 507
initial value 97.933750
iter 10 value 93.792066
final value 93.792058
converged
Fitting Repeat 3
# weights: 507
initial value 96.799977
iter 10 value 93.804890
final value 93.804883
converged
Fitting Repeat 4
# weights: 507
initial value 95.154924
final value 94.052910
converged
Fitting Repeat 5
# weights: 507
initial value 106.074552
iter 10 value 88.092529
iter 20 value 86.924539
iter 30 value 86.923632
iter 40 value 86.855151
final value 86.854764
converged
Fitting Repeat 1
# weights: 103
initial value 103.568335
iter 10 value 94.736027
iter 20 value 94.056609
iter 30 value 93.657182
iter 40 value 91.232428
iter 50 value 90.091876
iter 60 value 88.894253
iter 70 value 86.676614
iter 80 value 86.000175
iter 90 value 85.861916
iter 100 value 85.660062
final value 85.660062
stopped after 100 iterations
Fitting Repeat 2
# weights: 103
initial value 104.502289
iter 10 value 94.044091
iter 20 value 87.962889
iter 30 value 86.945752
iter 40 value 86.317481
iter 50 value 86.287896
iter 60 value 86.286257
final value 86.286120
converged
Fitting Repeat 3
# weights: 103
initial value 99.943335
iter 10 value 94.055333
iter 20 value 93.796046
iter 30 value 93.748840
iter 40 value 93.742246
iter 50 value 93.664572
iter 60 value 90.965199
iter 70 value 87.976968
iter 80 value 87.218377
iter 90 value 86.049281
iter 100 value 85.652008
final value 85.652008
stopped after 100 iterations
Fitting Repeat 4
# weights: 103
initial value 103.374177
iter 10 value 93.988851
iter 20 value 90.014990
iter 30 value 88.534919
iter 40 value 88.307074
iter 50 value 87.447228
iter 60 value 86.191249
iter 70 value 85.850898
iter 80 value 85.839394
final value 85.835495
converged
Fitting Repeat 5
# weights: 103
initial value 102.371120
iter 10 value 94.062103
iter 20 value 94.009432
iter 30 value 86.977277
iter 40 value 85.797979
iter 50 value 85.399731
iter 60 value 85.346400
final value 85.340097
converged
Fitting Repeat 1
# weights: 305
initial value 111.941222
iter 10 value 94.037881
iter 20 value 91.884699
iter 30 value 87.918729
iter 40 value 85.378159
iter 50 value 85.041137
iter 60 value 84.878263
iter 70 value 84.811111
iter 80 value 84.547803
iter 90 value 83.718763
iter 100 value 82.843282
final value 82.843282
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 113.686476
iter 10 value 94.077821
iter 20 value 93.900546
iter 30 value 92.957773
iter 40 value 89.700965
iter 50 value 88.965026
iter 60 value 88.731462
iter 70 value 87.981873
iter 80 value 87.051708
iter 90 value 82.903895
iter 100 value 82.152714
final value 82.152714
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 106.238767
iter 10 value 94.269979
iter 20 value 93.521318
iter 30 value 92.325658
iter 40 value 87.573276
iter 50 value 85.753901
iter 60 value 84.537204
iter 70 value 83.386694
iter 80 value 82.470309
iter 90 value 81.770643
iter 100 value 81.506785
final value 81.506785
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 103.049945
iter 10 value 93.392180
iter 20 value 88.494441
iter 30 value 86.931214
iter 40 value 86.208330
iter 50 value 85.702148
iter 60 value 84.875579
iter 70 value 84.564539
iter 80 value 83.352576
iter 90 value 82.140590
iter 100 value 81.822398
final value 81.822398
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.218785
iter 10 value 93.965953
iter 20 value 89.786373
iter 30 value 87.034492
iter 40 value 86.449107
iter 50 value 86.304515
iter 60 value 84.955499
iter 70 value 83.877758
iter 80 value 83.134988
iter 90 value 82.511080
iter 100 value 82.101022
final value 82.101022
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 122.658076
iter 10 value 94.066461
iter 20 value 91.301542
iter 30 value 88.572613
iter 40 value 86.732628
iter 50 value 85.895281
iter 60 value 85.354674
iter 70 value 84.092149
iter 80 value 83.526157
iter 90 value 82.669582
iter 100 value 81.927107
final value 81.927107
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 133.306072
iter 10 value 93.719824
iter 20 value 89.051991
iter 30 value 87.972653
iter 40 value 85.900266
iter 50 value 85.640834
iter 60 value 84.938089
iter 70 value 84.111140
iter 80 value 83.492888
iter 90 value 82.391830
iter 100 value 81.918087
final value 81.918087
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 109.560829
iter 10 value 94.197332
iter 20 value 87.366267
iter 30 value 86.678902
iter 40 value 86.388269
iter 50 value 85.587311
iter 60 value 84.427798
iter 70 value 83.769593
iter 80 value 83.120193
iter 90 value 82.560394
iter 100 value 82.275052
final value 82.275052
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 105.079627
iter 10 value 96.475575
iter 20 value 90.049113
iter 30 value 85.654124
iter 40 value 84.632576
iter 50 value 83.281339
iter 60 value 82.662461
iter 70 value 82.239927
iter 80 value 82.020460
iter 90 value 81.904489
iter 100 value 81.675037
final value 81.675037
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 135.274661
iter 10 value 94.087933
iter 20 value 93.717101
iter 30 value 91.382368
iter 40 value 87.712267
iter 50 value 84.179049
iter 60 value 82.408459
iter 70 value 81.564575
iter 80 value 81.230140
iter 90 value 81.155390
iter 100 value 81.033365
final value 81.033365
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 94.254482
final value 94.054392
converged
Fitting Repeat 2
# weights: 103
initial value 99.806534
final value 94.054559
converged
Fitting Repeat 3
# weights: 103
initial value 98.803419
final value 94.054312
converged
Fitting Repeat 4
# weights: 103
initial value 101.127454
final value 94.054500
converged
Fitting Repeat 5
# weights: 103
initial value 96.132928
iter 10 value 94.054412
iter 20 value 94.036381
iter 30 value 89.607660
iter 40 value 88.945660
iter 50 value 88.868519
iter 60 value 88.866457
iter 70 value 87.261833
iter 80 value 87.228101
iter 90 value 87.227620
iter 100 value 87.046791
final value 87.046791
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 95.018259
iter 10 value 93.908592
iter 20 value 93.907995
iter 30 value 93.883347
iter 40 value 93.882201
iter 50 value 91.154378
iter 60 value 87.636602
iter 70 value 86.162063
iter 80 value 85.885521
iter 90 value 85.734843
iter 100 value 85.004032
final value 85.004032
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 98.559857
iter 10 value 94.057776
iter 20 value 94.053061
iter 30 value 93.813263
iter 40 value 92.754413
iter 50 value 88.443617
iter 60 value 87.908040
final value 87.907629
converged
Fitting Repeat 3
# weights: 305
initial value 99.276702
iter 10 value 94.056112
iter 20 value 94.052916
iter 30 value 90.268821
iter 40 value 90.060360
final value 90.060328
converged
Fitting Repeat 4
# weights: 305
initial value 96.013979
iter 10 value 94.058369
iter 20 value 93.896435
iter 30 value 87.447335
iter 40 value 87.440320
iter 50 value 87.439871
final value 87.439441
converged
Fitting Repeat 5
# weights: 305
initial value 108.754160
iter 10 value 94.057636
iter 20 value 94.041925
iter 30 value 93.731242
iter 40 value 86.133689
iter 50 value 85.883108
final value 85.876172
converged
Fitting Repeat 1
# weights: 507
initial value 96.734541
iter 10 value 94.046562
iter 20 value 94.039446
final value 94.038831
converged
Fitting Repeat 2
# weights: 507
initial value 121.072347
iter 10 value 93.813362
iter 20 value 93.809365
iter 30 value 93.805381
iter 40 value 93.675170
iter 50 value 86.401309
iter 60 value 85.153413
iter 70 value 84.975129
iter 80 value 84.974186
iter 90 value 84.973814
iter 100 value 84.973181
final value 84.973181
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 110.566049
iter 10 value 93.868268
iter 20 value 93.653123
iter 30 value 93.624045
iter 40 value 93.620464
final value 93.619319
converged
Fitting Repeat 4
# weights: 507
initial value 94.828752
iter 10 value 93.867921
iter 20 value 92.332350
iter 30 value 88.725540
iter 40 value 88.125841
final value 88.125809
converged
Fitting Repeat 5
# weights: 507
initial value 114.516050
iter 10 value 93.892257
iter 20 value 93.875355
iter 30 value 93.844290
iter 40 value 93.838191
iter 50 value 93.744832
iter 60 value 93.639237
iter 70 value 93.626660
iter 80 value 93.626419
iter 90 value 93.625572
final value 93.625520
converged
Fitting Repeat 1
# weights: 103
initial value 109.273212
final value 94.484211
converged
Fitting Repeat 2
# weights: 103
initial value 109.027025
iter 10 value 94.473118
iter 10 value 94.473118
iter 10 value 94.473118
final value 94.473118
converged
Fitting Repeat 3
# weights: 103
initial value 97.624657
final value 94.484211
converged
Fitting Repeat 4
# weights: 103
initial value 106.397426
final value 94.484211
converged
Fitting Repeat 5
# weights: 103
initial value 101.246057
final value 94.484211
converged
Fitting Repeat 1
# weights: 305
initial value 114.582495
final value 94.482478
converged
Fitting Repeat 2
# weights: 305
initial value 96.050900
iter 10 value 82.962878
iter 20 value 81.271987
iter 30 value 81.230746
iter 30 value 81.230746
iter 30 value 81.230746
final value 81.230746
converged
Fitting Repeat 3
# weights: 305
initial value 103.102995
final value 94.354396
converged
Fitting Repeat 4
# weights: 305
initial value 102.235845
final value 94.354396
converged
Fitting Repeat 5
# weights: 305
initial value 114.384027
final value 94.484211
converged
Fitting Repeat 1
# weights: 507
initial value 114.212165
final value 94.354396
converged
Fitting Repeat 2
# weights: 507
initial value 120.545301
iter 10 value 102.129187
iter 20 value 94.354841
final value 94.354396
converged
Fitting Repeat 3
# weights: 507
initial value 101.107319
iter 10 value 94.321512
iter 20 value 92.023730
iter 30 value 83.249069
iter 40 value 81.400352
iter 50 value 81.396627
final value 81.396620
converged
Fitting Repeat 4
# weights: 507
initial value 110.597702
final value 94.484210
converged
Fitting Repeat 5
# weights: 507
initial value 97.020826
final value 94.484210
converged
Fitting Repeat 1
# weights: 103
initial value 105.762082
iter 10 value 94.455128
iter 20 value 93.749575
iter 30 value 87.526847
iter 40 value 84.680029
iter 50 value 82.829793
iter 60 value 81.335516
iter 70 value 81.315281
iter 80 value 81.311349
final value 81.311343
converged
Fitting Repeat 2
# weights: 103
initial value 101.644935
iter 10 value 88.557514
iter 20 value 85.295322
iter 30 value 83.289644
iter 40 value 83.212175
iter 50 value 83.145637
iter 60 value 83.035632
iter 70 value 82.955675
iter 80 value 82.926919
final value 82.926916
converged
Fitting Repeat 3
# weights: 103
initial value 96.631806
iter 10 value 94.236717
iter 20 value 87.560272
iter 30 value 87.260561
iter 40 value 86.548542
iter 50 value 83.498699
iter 60 value 82.932947
iter 70 value 82.841865
iter 80 value 82.625503
iter 90 value 82.497250
final value 82.496856
converged
Fitting Repeat 4
# weights: 103
initial value 102.501075
iter 10 value 87.267075
iter 20 value 83.341119
iter 30 value 83.024947
iter 40 value 82.817605
iter 50 value 82.643291
iter 60 value 82.539996
iter 70 value 82.455969
iter 80 value 82.368538
iter 90 value 82.356483
iter 90 value 82.356482
iter 90 value 82.356482
final value 82.356482
converged
Fitting Repeat 5
# weights: 103
initial value 109.160513
iter 10 value 94.487053
iter 20 value 89.405393
iter 30 value 84.343899
iter 40 value 83.587230
iter 50 value 83.483616
iter 60 value 83.342950
final value 83.326476
converged
Fitting Repeat 1
# weights: 305
initial value 100.202336
iter 10 value 94.818056
iter 20 value 88.965878
iter 30 value 85.002922
iter 40 value 84.604406
iter 50 value 83.926782
iter 60 value 80.564532
iter 70 value 80.220122
iter 80 value 80.168031
iter 90 value 80.044908
iter 100 value 79.960138
final value 79.960138
stopped after 100 iterations
Fitting Repeat 2
# weights: 305
initial value 106.719782
iter 10 value 85.911729
iter 20 value 84.666825
iter 30 value 83.242606
iter 40 value 81.314382
iter 50 value 80.749856
iter 60 value 80.624012
iter 70 value 80.243597
iter 80 value 79.808493
iter 90 value 79.761138
iter 100 value 79.757502
final value 79.757502
stopped after 100 iterations
Fitting Repeat 3
# weights: 305
initial value 103.090335
iter 10 value 95.020189
iter 20 value 94.005220
iter 30 value 86.426526
iter 40 value 83.407911
iter 50 value 82.588043
iter 60 value 82.502965
iter 70 value 80.993646
iter 80 value 80.079954
iter 90 value 79.597149
iter 100 value 79.570946
final value 79.570946
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 111.937280
iter 10 value 94.273735
iter 20 value 86.898476
iter 30 value 83.545899
iter 40 value 82.031249
iter 50 value 81.285679
iter 60 value 81.201367
iter 70 value 81.027560
iter 80 value 80.141442
iter 90 value 79.722790
iter 100 value 79.501402
final value 79.501402
stopped after 100 iterations
Fitting Repeat 5
# weights: 305
initial value 101.158176
iter 10 value 94.206562
iter 20 value 88.911817
iter 30 value 87.957659
iter 40 value 87.371021
iter 50 value 85.007943
iter 60 value 83.000133
iter 70 value 81.796351
iter 80 value 80.272823
iter 90 value 79.960701
iter 100 value 79.762871
final value 79.762871
stopped after 100 iterations
Fitting Repeat 1
# weights: 507
initial value 105.164665
iter 10 value 89.942329
iter 20 value 83.291980
iter 30 value 82.049747
iter 40 value 81.538482
iter 50 value 80.339872
iter 60 value 79.866626
iter 70 value 79.682947
iter 80 value 79.622985
iter 90 value 79.348413
iter 100 value 79.180324
final value 79.180324
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 103.055341
iter 10 value 94.965983
iter 20 value 90.987689
iter 30 value 85.027056
iter 40 value 81.433995
iter 50 value 80.638446
iter 60 value 80.375931
iter 70 value 80.251425
iter 80 value 80.234649
iter 90 value 80.182720
iter 100 value 80.007676
final value 80.007676
stopped after 100 iterations
Fitting Repeat 3
# weights: 507
initial value 132.414230
iter 10 value 95.315159
iter 20 value 94.114805
iter 30 value 85.140347
iter 40 value 83.524044
iter 50 value 83.199309
iter 60 value 82.759000
iter 70 value 81.468051
iter 80 value 80.570196
iter 90 value 80.394524
iter 100 value 79.944081
final value 79.944081
stopped after 100 iterations
Fitting Repeat 4
# weights: 507
initial value 112.093370
iter 10 value 94.686858
iter 20 value 93.756535
iter 30 value 90.314013
iter 40 value 86.245216
iter 50 value 83.113513
iter 60 value 82.162750
iter 70 value 81.762142
iter 80 value 80.673297
iter 90 value 79.938458
iter 100 value 79.240894
final value 79.240894
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 128.831559
iter 10 value 99.863442
iter 20 value 91.936175
iter 30 value 88.729028
iter 40 value 83.020783
iter 50 value 82.684049
iter 60 value 82.296674
iter 70 value 82.209986
iter 80 value 81.679176
iter 90 value 80.686270
iter 100 value 80.261099
final value 80.261099
stopped after 100 iterations
Fitting Repeat 1
# weights: 103
initial value 104.942387
iter 10 value 94.474881
iter 10 value 94.474880
iter 10 value 94.474880
final value 94.474880
converged
Fitting Repeat 2
# weights: 103
initial value 99.886644
final value 94.489962
converged
Fitting Repeat 3
# weights: 103
initial value 99.308360
final value 94.485911
converged
Fitting Repeat 4
# weights: 103
initial value 98.380218
final value 94.485874
converged
Fitting Repeat 5
# weights: 103
initial value 97.711720
final value 94.485826
converged
Fitting Repeat 1
# weights: 305
initial value 109.052378
iter 10 value 94.488781
iter 20 value 94.484261
final value 94.484221
converged
Fitting Repeat 2
# weights: 305
initial value 113.527416
iter 10 value 94.489380
iter 20 value 94.484538
iter 30 value 94.484394
iter 40 value 93.676916
iter 50 value 83.441818
iter 60 value 80.584118
iter 70 value 80.527243
final value 80.527225
converged
Fitting Repeat 3
# weights: 305
initial value 95.344972
iter 10 value 94.489170
iter 20 value 94.484310
iter 30 value 94.424971
iter 40 value 92.752982
iter 50 value 87.311397
iter 60 value 85.856882
iter 70 value 84.911103
iter 80 value 84.774394
iter 90 value 84.757099
iter 100 value 84.661311
final value 84.661311
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 95.625321
iter 10 value 94.320666
iter 20 value 94.319959
iter 30 value 94.313386
iter 40 value 94.312032
iter 50 value 94.311237
iter 60 value 93.587821
iter 70 value 93.568753
iter 80 value 92.708738
iter 90 value 92.708625
final value 92.708621
converged
Fitting Repeat 5
# weights: 305
initial value 109.395564
iter 10 value 94.359344
iter 20 value 91.837074
iter 30 value 88.065256
iter 40 value 83.533193
iter 50 value 82.699546
iter 60 value 82.299463
iter 70 value 82.206138
final value 82.199564
converged
Fitting Repeat 1
# weights: 507
initial value 104.978197
iter 10 value 94.481196
iter 20 value 94.475578
iter 30 value 85.860029
iter 40 value 84.009522
iter 50 value 84.008974
iter 60 value 84.001960
iter 70 value 80.914232
iter 80 value 80.132491
iter 90 value 80.127380
iter 100 value 79.452168
final value 79.452168
stopped after 100 iterations
Fitting Repeat 2
# weights: 507
initial value 102.673928
iter 10 value 91.783751
iter 20 value 81.749307
iter 30 value 81.407929
final value 81.407009
converged
Fitting Repeat 3
# weights: 507
initial value 100.851412
iter 10 value 94.362247
iter 20 value 94.354616
final value 94.354527
converged
Fitting Repeat 4
# weights: 507
initial value 106.359268
iter 10 value 94.353343
iter 20 value 94.348288
iter 30 value 91.544291
iter 40 value 88.323744
iter 50 value 88.073355
iter 60 value 87.599209
iter 70 value 87.409854
iter 80 value 87.408732
iter 90 value 83.978835
iter 100 value 81.215195
final value 81.215195
stopped after 100 iterations
Fitting Repeat 5
# weights: 507
initial value 109.457073
iter 10 value 94.362131
iter 20 value 94.354292
iter 30 value 92.205383
iter 40 value 81.256282
iter 50 value 81.205901
iter 60 value 81.205788
iter 70 value 81.203380
iter 80 value 81.201509
iter 90 value 80.319606
iter 100 value 79.748977
final value 79.748977
stopped after 100 iterations
Fitting Repeat 1
# weights: 305
initial value 154.296939
iter 10 value 117.895917
iter 20 value 116.567115
iter 30 value 107.010799
iter 40 value 107.004727
iter 50 value 107.004621
final value 107.004583
converged
Fitting Repeat 2
# weights: 305
initial value 140.830949
iter 10 value 117.870564
iter 20 value 117.866235
final value 117.866073
converged
Fitting Repeat 3
# weights: 305
initial value 157.590191
iter 10 value 117.895336
iter 20 value 115.210025
iter 30 value 107.428798
iter 40 value 104.251459
iter 50 value 103.926160
iter 60 value 103.919259
iter 70 value 103.895296
iter 80 value 103.851789
iter 90 value 103.611405
iter 100 value 103.558964
final value 103.558964
stopped after 100 iterations
Fitting Repeat 4
# weights: 305
initial value 128.241605
iter 10 value 117.210692
iter 20 value 117.206686
final value 117.206618
converged
Fitting Repeat 5
# weights: 305
initial value 129.044388
iter 10 value 117.763616
iter 20 value 117.744721
iter 30 value 113.042371
iter 40 value 107.446928
iter 50 value 100.478001
iter 60 value 99.967716
iter 70 value 99.678283
iter 80 value 99.481000
iter 90 value 99.455378
iter 100 value 99.454631
final value 99.454631
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 -- Mon Mar 9 00:14:45 2026
***********************************************
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
40.330 0.827 102.654
HPiP.Rcheck/HPiP-Ex.timings
| name | user | system | elapsed | |
| FSmethod | 32.413 | 0.586 | 33.001 | |
| FreqInteractors | 0.424 | 0.037 | 0.461 | |
| calculateAAC | 0.033 | 0.000 | 0.033 | |
| calculateAutocor | 0.267 | 0.018 | 0.286 | |
| calculateCTDC | 0.072 | 0.000 | 0.073 | |
| calculateCTDD | 0.448 | 0.003 | 0.451 | |
| calculateCTDT | 0.140 | 0.001 | 0.140 | |
| calculateCTriad | 0.364 | 0.006 | 0.369 | |
| calculateDC | 0.084 | 0.005 | 0.089 | |
| calculateF | 0.290 | 0.001 | 0.292 | |
| calculateKSAAP | 0.096 | 0.007 | 0.102 | |
| calculateQD_Sm | 1.835 | 0.025 | 1.860 | |
| calculateTC | 1.442 | 0.144 | 1.587 | |
| calculateTC_Sm | 0.275 | 0.004 | 0.278 | |
| corr_plot | 33.620 | 0.389 | 34.009 | |
| enrichfindP | 0.503 | 0.039 | 15.619 | |
| enrichfind_hp | 0.040 | 0.002 | 1.066 | |
| enrichplot | 0.488 | 0.005 | 0.494 | |
| filter_missing_values | 0.002 | 0.000 | 0.001 | |
| getFASTA | 0.407 | 0.014 | 3.829 | |
| getHPI | 0.001 | 0.001 | 0.002 | |
| get_negativePPI | 0.002 | 0.001 | 0.004 | |
| get_positivePPI | 0.001 | 0.000 | 0.000 | |
| impute_missing_data | 0.003 | 0.001 | 0.003 | |
| plotPPI | 0.094 | 0.002 | 0.097 | |
| pred_ensembel | 12.496 | 0.108 | 11.317 | |
| var_imp | 34.879 | 0.521 | 35.433 | |