pl.pe.parest

Module Contents

class pl.pe.parest.ParEst(models_folder="Models", working_folder="Results", sim_data_folder="param_estim_data", sim_plots_folder="param_estim_plots")[source]

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

__init__(models_folder="Models", working_folder="Results", sim_data_folder="param_estim_data", sim_plots_folder="param_estim_plots")[source]
run(config_file)[source]
generate_data(simulator, model, inputdir, cluster, local_cpus, runs, outputdir, sim_data_dir)[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
  • cluster – local, lsf for load sharing facility, sge for sun grid engine
  • local_cpus – the number of cpu
  • runs – the number of fits to perform
  • outputdir – the directory to store the results
  • sim_data_dir – the directory containing the simulation data sets
Returns:

True if the task was completed successfully, False otherwise.
analyse_data(simulator, model, inputdir, outputdir, fileout_final_estims, fileout_all_estims, fileout_param_estim_best_fits_details, fileout_param_estim_details, fileout_param_estim_summary, sim_plots_dir, best_fits_percent, data_point_num, cluster="local", plot_2d_66cl_corr=False, plot_2d_95cl_corr=False, plot_2d_99cl_corr=False, logspace=True, scientific_notation=True)[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 simulation data
  • outputdir – the directory to store the results
  • fileout_final_estims – the name of the file containing final parameter sets with the objective value
  • fileout_all_estims – the name of the file containing all the parameter sets with the objective value
  • fileout_param_estim_best_fits_details – the file containing the statistics for the best fits analysis
  • fileout_param_estim_details – the file containing the statistics for the PLE analysis
  • fileout_param_estim_summary – the name of the file containing the summary for the parameter estimation
  • sim_plots_dir – the directory of the simulation plots
  • best_fits_percent – the percent to consider for the best fits
  • data_point_num – the number of data points
  • cluster – local, lsf for Load Sharing Facility, sge for Sun Grid Engine.
  • plot_2d_66cl_corr – True if 2 dim plots for the parameter sets within 66% should be plotted
  • plot_2d_95cl_corr – True if 2 dim plots for the parameter sets within 95% should be plotted
  • plot_2d_99cl_corr – True if 2 dim plots for the parameter sets within 99% should be plotted
  • logspace – True if parameters should be plotted in log space
  • scientific_notation – True if axis labels should be plotted in scientific notation
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 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]