2.2. Command line interface

To excecute a parameter fitting problem from the command line interface (CLI) you need to specify your optimization problem in the PEtab format, which is built around SBML and TSV files. If you also want to customise upper and lower boundaries for model species, you can provide an additional species table (see species_Vinod_FEBS2015.tsv as an example).

The sbml2julia CLI allows you to specify the following optimization options:

  • -t, –t_steps: number of time-discretization steps. Default None.

  • -n, –n_starts: number of multistarts. Default 1.

  • -i, –infer_ic_from_sbml: infer initial conditions which are not specified in the PEtab condition table from SBML. Default False.

  • -o, –optimizer_options: optimization solver options. Default {}.

  • -c, –custom_code_dict: dict with replaced code as keys and replacement code as values. Default {}.

  • -d, –out_dir: output directory for julia_code, results and plot. Default './results/'.

  • -p, –plot_obs: list of observables to be plotted. Default all, i.e. [].

The problem is then specified and solved via:

user@bash:/$ sbml2julia optimize 'my_petab_promlem.yaml' -t 100 -n 1 -i 'False' -o {} -c {} -d './results' -p '[]'

The results can be found in the output directory given to the -d argument.

2.2.1. Choosing an HSL linear solver

Optionally, the optimizer_options attribute can be used to specify the linear solver used within Ipopt. For example:

user@bash:/$ sbml2julia optimize 'my_petab_promlem.yaml' -t 100 -n 1 -i 'False' -o '{linear_solver: ma57}' -c {} -d './results' -p '[]'