library(hyperion)
#>
#>
#> ── pharos configuration ────────────────────────────────────────────────────────
#> ✔ pharos.toml found: /data/user-homes/tariq/projects/prism-pkgdocs-build/installed-pkgs/2026-03-02/hyperion_0.3.2/vignettes/pharos.toml
#> ── hyperion options ────────────────────────────────────────────────────────────
#> ✔ hyperion.significant_number_display : 4
#> ── hyperion nonmem object options ──────────────────────────────────────────────
#> ✔ hyperion.nonmem_model.show_included_columns : FALSE
#> ✔ hyperion.nonmem_summary.rse_threshold : 50
#> ✔ hyperion.nonmem_summary.shrinkage_threshold : 30
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
test_data_dir <- system.file("extdata", package = "hyperion")
get_gradients(file.path(test_data_dir, "models", "onecmt", "run001"))
#> iteration method GRD.THETA1. GRD.THETA2. GRD.THETA3. GRD.ETA1.
#> 1 0 FOCE -95.24010000 -1.54473e+02 -50.3937000 -1.85651e+01
#> 2 5 FOCE -5.65185000 -1.31776e+01 -2.3672200 -1.17689e+00
#> 3 10 FOCE -0.05381990 -1.24398e+00 -0.2432470 2.56664e-02
#> 4 13 FOCE 0.00312907 -8.27509e-04 0.0013005 1.92388e-04
#> GRD.ETA2. GRD.EPS1.
#> 1 -5.83561e+01 16.98700000
#> 2 -4.06991e+00 1.21143000
#> 3 1.51531e-01 -0.01604710
#> 4 1.49836e-04 0.00063828
get_gradients(file.path(test_data_dir, "models", "onecmt", "run001"))
#> iteration method GRD.THETA1. GRD.THETA2. GRD.THETA3. GRD.ETA1.
#> 1 0 FOCE -95.24010000 -1.54473e+02 -50.3937000 -1.85651e+01
#> 2 5 FOCE -5.65185000 -1.31776e+01 -2.3672200 -1.17689e+00
#> 3 10 FOCE -0.05381990 -1.24398e+00 -0.2432470 2.56664e-02
#> 4 13 FOCE 0.00312907 -8.27509e-04 0.0013005 1.92388e-04
#> GRD.ETA2. GRD.EPS1.
#> 1 -5.83561e+01 16.98700000
#> 2 -4.06991e+00 1.21143000
#> 3 1.51531e-01 -0.01604710
#> 4 1.49836e-04 0.00063828
get_gradients(file.path(test_data_dir, "models", "onecmt", "run001", "run001.grd"))
#> iteration method GRD.THETA1. GRD.THETA2. GRD.THETA3. GRD.ETA1.
#> 1 0 FOCE -95.24010000 -1.54473e+02 -50.3937000 -1.85651e+01
#> 2 5 FOCE -5.65185000 -1.31776e+01 -2.3672200 -1.17689e+00
#> 3 10 FOCE -0.05381990 -1.24398e+00 -0.2432470 2.56664e-02
#> 4 13 FOCE 0.00312907 -8.27509e-04 0.0013005 1.92388e-04
#> GRD.ETA2. GRD.EPS1.
#> 1 -5.83561e+01 16.98700000
#> 2 -4.06991e+00 1.21143000
#> 3 1.51531e-01 -0.01604710
#> 4 1.49836e-04 0.00063828
get_gradients(file.path(test_data_dir, "models", "onecmt", "run002"))
#> iteration method GRD.TVCL. GRD.TVV. GRD.TVKA. GRD.OM1..TVCL..
#> 1 0 FOCE -2.38364e-01 4.34772e-01 -3.34223e-01 3.33661e-02
#> 2 5 FOCE 1.23194e+00 -9.14972e-01 3.77112e-01 -4.11332e-01
#> 3 10 FOCE 1.84041e-03 -2.25898e-03 -2.12048e-03 2.22174e-03
#> 4 15 FOCE 2.41066e-05 1.73623e-05 3.20979e-06 2.26613e-06
#> GRD.OM2..TVV.. GRD.OM3..TVKA.. GRD.EPS1. GRD.EPS2.
#> 1 0.114883000 -2.04802e+00 0.340024000 1.11603e+00
#> 2 0.991775000 2.96604e-01 1.926170000 5.00827e-01
#> 3 -0.001427710 2.96243e-03 0.015992400 2.34632e-03
#> 4 -0.000111782 -4.43439e-05 -0.000122955 1.27956e-05
get_gradients(file.path(test_data_dir, "models", "onecmt", "run002.mod"))
#> iteration method GRD.TVCL. GRD.TVV. GRD.TVKA. GRD.OM1..TVCL..
#> 1 0 FOCE -2.38364e-01 4.34772e-01 -3.34223e-01 3.33661e-02
#> 2 5 FOCE 1.23194e+00 -9.14972e-01 3.77112e-01 -4.11332e-01
#> 3 10 FOCE 1.84041e-03 -2.25898e-03 -2.12048e-03 2.22174e-03
#> 4 15 FOCE 2.41066e-05 1.73623e-05 3.20979e-06 2.26613e-06
#> GRD.OM2..TVV.. GRD.OM3..TVKA.. GRD.EPS1. GRD.EPS2.
#> 1 0.114883000 -2.04802e+00 0.340024000 1.11603e+00
#> 2 0.991775000 2.96604e-01 1.926170000 5.00827e-01
#> 3 -0.001427710 2.96243e-03 0.015992400 2.34632e-03
#> 4 -0.000111782 -4.43439e-05 -0.000122955 1.27956e-05
get_gradients(file.path(test_data_dir, "models", "onecmt", "run002", "run002.grd"))
#> iteration method GRD.TVCL. GRD.TVV. GRD.TVKA. GRD.OM1..TVCL..
#> 1 0 FOCE -2.38364e-01 4.34772e-01 -3.34223e-01 3.33661e-02
#> 2 5 FOCE 1.23194e+00 -9.14972e-01 3.77112e-01 -4.11332e-01
#> 3 10 FOCE 1.84041e-03 -2.25898e-03 -2.12048e-03 2.22174e-03
#> 4 15 FOCE 2.41066e-05 1.73623e-05 3.20979e-06 2.26613e-06
#> GRD.OM2..TVV.. GRD.OM3..TVKA.. GRD.EPS1. GRD.EPS2.
#> 1 0.114883000 -2.04802e+00 0.340024000 1.11603e+00
#> 2 0.991775000 2.96604e-01 1.926170000 5.00827e-01
#> 3 -0.001427710 2.96243e-03 0.015992400 2.34632e-03
#> 4 -0.000111782 -4.43439e-05 -0.000122955 1.27956e-05
get_gradients(file.path(test_data_dir, "models", "onecmt", "run002_metadata.json"))
#> iteration method GRD.1. GRD.2. GRD.3. GRD.4.
#> 1 0 FOCE -2.38364e-01 4.34772e-01 -3.34223e-01 3.33661e-02
#> 2 5 FOCE 1.23194e+00 -9.14972e-01 3.77112e-01 -4.11332e-01
#> 3 10 FOCE 1.84041e-03 -2.25898e-03 -2.12048e-03 2.22174e-03
#> 4 15 FOCE 2.41066e-05 1.73623e-05 3.20979e-06 2.26613e-06
#> GRD.5. GRD.6. GRD.7. GRD.8.
#> 1 0.114883000 -2.04802e+00 0.340024000 1.11603e+00
#> 2 0.991775000 2.96604e-01 1.926170000 5.00827e-01
#> 3 -0.001427710 2.96243e-03 0.015992400 2.34632e-03
#> 4 -0.000111782 -4.43439e-05 -0.000122955 1.27956e-05