Example 7: PK Model, Exhaustive Omega Search

Example 7 uses dataExample1.csv for an Exhaustive search of omega structures across candidate models.

The template file can be downloaded here and the tokens file here.

It is recommended that the user set the directories to something appropriate for their environment. If directories are not set, the default is:

{user_dir}\pydarwin\{project_name}

where {user_dir} is the user’s home directory and {project_name} is the name of the project.

The options file looks like:

{
  "author": "Certara",
  "algorithm": "EXHAUSTIVE",
  "exhaustive_batch_size": 500,
  "num_parallel": 4,
  "crash_value": 99999999,
  "random_seed": 11,
  "penalty": {
    "theta": 10,
    "omega": 10,
    "sigma": 10,
    "convergence": 100,
    "covariance": 100,
    "correlation": 100,
    "condition_number": 100,
    "non_influential_tokens": 0.00001
  },
  "search_omega_bands": true,
  "max_omega_band_width": 1,
  "search_omega_sub_matrix": true,
  "max_omega_sub_matrix": 2,
  "remove_run_dir": false,
  "nmfe_path": "c:/nm74g64/util/nmfe74.bat",
  "model_run_timeout": 1200
}

and can be downloaded here.

Note the usage of additional options for omega search: “search_omega_bands”, “max_omega_sub_matrix”, “search_omega_sub_matrix”, and “max_omega_sub_matrix”.

Execute Search

Usage details for starting a search in pyDarwin can be found here.

See “Examples” for additional details about accessing example files.

Initialization output should look like:

[10:49:51] Including search of band OMEGA, with width up to 1
[10:49:51] Including search for OMEGA submatrices, with size up to 2
[10:49:51] Search start time = Wed Jan  4 10:49:51 2023
[10:49:51] Total of 32 to be run in exhaustive search
[10:49:51] NMFE found: c:/nm74g64/util/nmfe74.bat
[10:49:51] Not using Post Run R code
[10:49:51] Not using Post Run Python code
[10:49:51] Checking files in C:\Users\jcraig\pydarwin\Example7\temp\0\01
[10:49:51] Data set # 1 was found: C:\Workspace\Example7/dataExample1.csv

and the final output should appear similar to:

[10:56:58] Iteration = 0, Model    32,           Done,    fitness = 4873.801,    message = No important warnings
[10:57:00] Iteration = 0, Model    30,           Done,    fitness = 4892.377,    message = No important warnings
[10:57:02] Iteration = 0, Model    29,           Done,    fitness = 4862.237,    message = No important warnings
[10:57:44] Iteration = 0, Model    31,           Done,    fitness = 4959.865,    message = No important warnings
[10:57:44] Current Best fitness = 4838.492760373933
[10:57:44] Final output from best model is in .\Example7\output\FinalResultFile.lst
[10:57:44] Number of unique models to best model = 6
[10:57:44] Time to best model = 0.5 minutes
[10:57:44] Best overall fitness = 4838.492760, iteration 0, model 3
[10:57:44] Elapsed time = 7.9 minutes