Source code for petab.visualize.data_overview

"""
Functions for creating an overview report of a PEtab problem
"""

from pathlib import Path
from shutil import copyfile
from typing import Union

import pandas as pd
import petab
from petab.C import *

__all__ = ['create_report']


[docs]def create_report( problem: petab.Problem, model_name: str, output_path: Union[str, Path] = '' ) -> None: """Create an HTML overview data / model overview report Arguments: problem: PEtab problem model_name: Name of the model, used for file name for report output_path: Output directory """ template_dir = Path(__file__).absolute().parent / 'templates' output_path = Path(output_path) template_file = "report.html" data_per_observable = get_data_per_observable(problem.measurement_df) num_conditions = len(problem.condition_df.index) # Setup template engine import jinja2 template_loader = jinja2.FileSystemLoader(searchpath=template_dir) template_env = jinja2.Environment(loader=template_loader) template = template_env.get_template(template_file) # Render and save output_text = template.render(problem=problem, model_name=model_name, data_per_observable=data_per_observable, num_conditions=num_conditions) with open(output_path / f'{model_name}.html', 'w') as html_file: html_file.write(output_text) copyfile(template_dir / 'mystyle.css', output_path / 'mystyle.css')
def get_data_per_observable(measurement_df: pd.DataFrame) -> pd.DataFrame: """Get table with number of data points per observable and condition Arguments: measurement_df: PEtab measurement data frame Returns: Pivot table with number of data points per observable and condition """ my_measurements = measurement_df.copy() index = [SIMULATION_CONDITION_ID] if PREEQUILIBRATION_CONDITION_ID in my_measurements: my_measurements[PREEQUILIBRATION_CONDITION_ID].fillna('', inplace=True) index.append(PREEQUILIBRATION_CONDITION_ID) data_per_observable = pd.pivot_table( my_measurements, values=MEASUREMENT, aggfunc='count', index=index, columns=[OBSERVABLE_ID], fill_value=0) # Add row and column sums data_per_observable.loc['SUM', :] = data_per_observable.sum(axis=0).values data_per_observable['SUM'] = data_per_observable.sum(axis=1).values data_per_observable = data_per_observable.astype(int) return data_per_observable