"""
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] = (
my_measurements[PREEQUILIBRATION_CONDITION_ID]
.astype("object")
.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