petab.visualize.helper_functions

This file should contain the functions, which PEtab internally needs for plotting, but which are not meant to be used by non-developers and should hence not be directly visible/usable when using import petab.visualize

Functions

check_vis_spec_consistency(dataset_id_list, …)	Helper function for plotting data and simulations, which check the visualization setting, if no visualization specification file is provided.
create_dataset_id_list(simcond_id_list, …)
create_figure(uni_plot_ids)	Helper function for plotting data and simulations, open figure and axes
get_data_to_plot(vis_spec, m_data, …)	group the data, which should be plotted and save it in pd.dataframe called ‘ms’.
get_default_vis_specs(exp_data, exp_conditions)	Helper function for plotting data and simulations, which creates a default visualization table.
handle_dataset_plot(i_visu_spec, ind_plot, …)
import_from_files(data_file_path, …)	Helper function for plotting data and simulations, which imports data from PEtab files.

petab.visualize.helper_functions.check_vis_spec_consistency(dataset_id_list, sim_cond_id_list, sim_cond_num_list, observable_id_list, observable_num_list, exp_data)

Helper function for plotting data and simulations, which check the visualization setting, if no visualization specification file is provided.

For documentation, see main function plot_data_and_simulation()

petab.visualize.helper_functions.create_figure(uni_plot_ids)

Helper function for plotting data and simulations, open figure and axes

Parameters:uni_plot_ids (ndarray) – Array with unique plot indices Returns:

• fig (Figure object of the created plot.)
• ax (Axis object of the created plot.)
• num_row (int, number of subplot rows)
• num_col (int, number of subplot columns)

petab.visualize.helper_functions.get_data_to_plot(vis_spec: pandas.core.frame.DataFrame, m_data: pandas.core.frame.DataFrame, simulation_data: pandas.core.frame.DataFrame, condition_ids: numpy.ndarray, i_visu_spec: int, col_id: str)

group the data, which should be plotted and save it in pd.dataframe called ‘ms’.

Parameters:

• vis_spec – pandas data frame, contains defined data format (visualization file)
• m_data – pandas data frame, contains defined data format (measurement file)
• simulation_data – pandas data frame, contains defined data format (simulation file)
• condition_ids – numpy array, containing all unique condition IDs which should be plotted in one figure (can be found in measurementData file, column simulationConditionId)
• i_visu_spec – int, current index (row number) of row which should be plotted in visualizationSpecification file
• col_id – str, the name of the column in visualization file, whose entries should be unique (depends on condition in column independentVariableName)

Returns:

pandas.DataFrame containing the data which should be plotted (Mean and Std)

Return type:

data_to_plot

petab.visualize.helper_functions.get_default_vis_specs(exp_data, exp_conditions, dataset_id_list=None, sim_cond_id_list=None, sim_cond_num_list=None, observable_id_list=None, observable_num_list=None, plotted_noise='MeanAndSD')

Helper function for plotting data and simulations, which creates a default visualization table.

For documentation, see main function plot_data_and_simulation()

petab.visualize.helper_functions.import_from_files(data_file_path, condition_file_path, visualization_file_path, simulation_file_path, dataset_id_list, sim_cond_id_list, sim_cond_num_list, observable_id_list, observable_num_list, plotted_noise)

Helper function for plotting data and simulations, which imports data from PEtab files.

For documentation, see main function plot_data_and_simulation()