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 (exp_data, …) |
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, …) |
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. |
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petab.visualize.helper_functions.
check_ex_exp_columns
(exp_data: pandas.core.frame.DataFrame, dataset_id_list: List[List[str]], sim_cond_id_list: List[List[str]], sim_cond_num_list: List[List[int]], observable_id_list: List[List[str]], observable_num_list: List[List[int]], exp_conditions: pandas.core.frame.DataFrame) → Tuple[pandas.core.frame.DataFrame, List[List[str]], Dict[KT, VT]]¶ Check the columns in measurement file, if non-mandotory columns does not exist, create default columns
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petab.visualize.helper_functions.
check_ex_visu_columns
(vis_spec: pandas.core.frame.DataFrame, dataset_id_list: List[List[str]], legend_dict: Dict[KT, VT]) → pandas.core.frame.DataFrame¶ Check the columns in Visu_Spec file, if non-mandotory columns does not exist, create default columns
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petab.visualize.helper_functions.
check_vis_spec_consistency
(exp_data: pandas.core.frame.DataFrame, dataset_id_list: Optional[List[List[str]]] = None, sim_cond_id_list: Optional[List[List[str]]] = None, sim_cond_num_list: Optional[List[List[int]]] = None, observable_id_list: Optional[List[List[str]]] = None, observable_num_list: Optional[List[List[int]]] = None) → str¶ 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()
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petab.visualize.helper_functions.
create_dataset_id_list
(simcond_id_list: List[List[str]], simcond_num_list: List[List[int]], observable_id_list: List[List[str]], observable_num_list: List[List[int]], exp_data: pandas.core.frame.DataFrame, exp_conditions: pandas.core.frame.DataFrame, group_by: str) → Tuple[pandas.core.frame.DataFrame, List[List[str]], Dict[KT, VT]]¶ Create dataset id list
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petab.visualize.helper_functions.
create_figure
(uni_plot_ids: numpy.ndarray, plots_to_file: bool) → Tuple[matplotlib.figure.Figure, Union[Dict[str, matplotlib.axes._subplots.AxesSubplot], np.ndarray[plt.Subplot]]]¶ 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.)
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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 – contains defined data format (measurement file)
- simulation_data – contains defined data format (simulation file)
- condition_ids – contains all unique condition IDs which should be plotted in one figure (can be found in measurementData file, column simulationConditionId)
- col_id – 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: contains the data which should be plotted (Mean and Std)
Return type: data_to_plot
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petab.visualize.helper_functions.
get_default_vis_specs
(exp_data: pandas.core.frame.DataFrame, exp_conditions: pandas.core.frame.DataFrame, dataset_id_list: Optional[List[List[str]]] = None, sim_cond_id_list: Optional[List[List[str]]] = None, sim_cond_num_list: Optional[List[List[int]]] = None, observable_id_list: Optional[List[List[str]]] = None, observable_num_list: Optional[List[List[int]]] = None, plotted_noise: Optional[str] = 'MeanAndSD') → Tuple[pandas.core.frame.DataFrame, pandas.core.frame.DataFrame]¶ Helper function for plotting data and simulations, which creates a default visualization table.
For documentation, see main function plot_data_and_simulation()
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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
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petab.visualize.helper_functions.
import_from_files
(data_file_path: str, condition_file_path: str, visualization_file_path: str, simulation_file_path: str, dataset_id_list: List[List[str]], sim_cond_id_list: List[List[str]], sim_cond_num_list: List[List[int]], observable_id_list: List[List[str]], observable_num_list: List[List[int]], plotted_noise: str) → Tuple[pandas.core.frame.DataFrame, pandas.core.frame.DataFrame, pandas.core.frame.DataFrame, pandas.core.frame.DataFrame]¶ Helper function for plotting data and simulations, which imports data from PEtab files.
For documentation, see main function plot_data_and_simulation()
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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