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_ex_exp_columns(exp_data, …) Check the columns in measurement file, if non-mandotory columns does not exist, create default columns
check_ex_visu_columns(vis_spec, …) Check the columns in Visu_Spec file, if non-mandotory columns does not exist, create default columns
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 dataset id list
create_figure(uni_plot_ids, plots_to_file) Helper function for plotting data and simulations, open figure and axes
get_data_to_plot(plot_spec, m_data, …) group the data, which should be plotted and return it as dataframe.
get_default_vis_specs(exp_data, exp_conditions) Helper function for plotting data and simulations, which creates a default visualization table.
handle_dataset_plot(plot_spec, ax, exp_data, …) Handle dataset plot
import_from_files(data_file_path, …) Helper function for plotting data and simulations, which imports data from PEtab files.
matches_plot_spec(df, col_id, x_value, str], …) constructs an index for subsetting of the dataframe according to what is specified in plot_spec.
petab.visualize.helper_functions.check_ex_exp_columns(exp_data, dataset_id_list, sim_cond_id_list, sim_cond_num_list, observable_id_list, observable_num_list, exp_conditions)

Check the columns in measurement file, if non-mandotory columns does not exist, create default columns

petab.visualize.helper_functions.check_ex_visu_columns(vis_spec, dataset_id_list, legend_dict)

Check the columns in Visu_Spec file, if non-mandotory columns does not exist, create default columns

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_dataset_id_list(simcond_id_list, simcond_num_list, observable_id_list, observable_num_list, exp_data, exp_conditions, group_by)

Create dataset id list

petab.visualize.helper_functions.create_figure(uni_plot_ids: numpy.ndarray, plots_to_file: bool)

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

Parameters:
  • uni_plot_ids – Array with unique plot indices
  • plots_to_file – Indicator if plots are saved to file
Returns:

  • fig (Figure object of the created plot.)
  • ax (Axis object of the created plot.)
petab.visualize.helper_functions.get_data_to_plot(plot_spec: pandas.core.series.Series, m_data: pandas.core.frame.DataFrame, simulation_data: pandas.core.frame.DataFrame, condition_ids: numpy.ndarray, col_id: str, simulation_field: str = 'simulation') → pandas.core.frame.DataFrame

group the data, which should be plotted and return it as dataframe.

Parameters:
  • plot_spec – information about 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)
  • col_id – str, the name of the column in visualization file, whose entries should be unique (depends on condition in column independentVariableName)
  • simulation_field – Column name in simulation_data that contains the actual simulation result.
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.handle_dataset_plot(plot_spec: pandas.core.series.Series, ax: matplotlib.axes._axes.Axes, exp_data: pandas.core.frame.DataFrame, exp_conditions: pandas.core.frame.DataFrame, sim_data: pandas.core.frame.DataFrame)

Handle dataset plot

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()

petab.visualize.helper_functions.matches_plot_spec(df: pandas.core.frame.DataFrame, col_id: str, x_value: Union[float, str], plot_spec: pandas.core.series.Series) → pandas.core.series.Series

constructs an index for subsetting of the dataframe according to what is specified in plot_spec.

Parameters:
  • df – pandas data frame to subset, can be from measurement file or simulation file
  • col_id – name of the column that will be used for indexing in x variable
  • x_value – subsetted x value
  • plot_spec – visualization spec from the visualization file
Returns:

boolean series that can be used for subsetting of the passed dataframe
Return type:

index