pl.sim.sim

Module Contents

class pl.sim.sim.Sim(models_folder="Models", working_folder="Results", sim_data_folder="simulate_data", sim_plots_folder="simulate_plots")[source]

This module provides the user with a complete pipeline of scripts for running model simulations

__init__(models_folder="Models", working_folder="Results", sim_data_folder="simulate_data", sim_plots_folder="simulate_plots")[source]
run(config_file)[source]
generate_data(simulator, model, inputdir, outputdir, cluster="local", local_cpus=2, runs=1)[source]

The first pipeline step: data generation.

Parameters:
  • simulator – the name of the simulator (e.g. Copasi)
  • model – the model to process
  • inputdir – the directory containing the model
  • outputdir – the directory containing the output files
  • cluster – local, lsf for Load Sharing Facility, sge for Sun Grid Engine.
  • local_cpus – the number of CPUs.
  • runs – the number of model simulation
Returns:

True if the task was completed successfully, False otherwise.
analyse_data(simulator, model, inputdir, outputdir, sim_plots_dir, exp_dataset, plot_exp_dataset, exp_dataset_alpha=1.0, cluster="local", local_cpus=2, xaxis_label="", yaxis_label="")[source]

The second pipeline step: data analysis.

Parameters:
  • simulator – the name of the simulator (e.g. Copasi)
  • model – the model name
  • inputdir – the directory containing the data to analyse
  • outputdir – the output directory containing the results
  • sim_plots_dir – the directory to save the plots
  • exp_dataset – the full path of the experimental data set
  • plot_exp_dataset – True if the experimental data set should also be plotted
  • exp_dataset_alpha – the alpha level for the data set
  • cluster – local, lsf for Load Sharing Facility, sge for Sun Grid Engine.
  • local_cpus – the number of CPUs.
  • xaxis_label – the label for the x axis (e.g. Time [min])
  • yaxis_label – the label for the y axis (e.g. Level [a.u.])
Returns:

True if the task was completed successfully, False otherwise.
generate_report(model, outputdir, sim_plots_folder)[source]

The third pipeline step: report generation.

Parameters:
  • model – the model name
  • outputdir – the output directory to store the report
  • sim_plots_folder – the folder containing the plots
Returns:

True if the task was completed successfully, False otherwise.
parse(my_dict)[source]