Documentation for Numpy and Tensor implementations of Epidemic Models

[GolanTrev]

• [ ] Make sure the functions and constants are in *.py files. E.g. models.py and auxiliary.py
• [ ] Documentation includes docstrings and header hints. E.g.

def run_model(params: Dict[str, Any], path: str, pop_geoid: pd.DataFrame, index_dict: Dict[Any, Any], net_type: str, date_interval: List[str], model: str = 'SEIR', num_sims: int = 36, initial_cond: Optional[pd.DataFrame] = None) -> pd.DataFrame: """ Runs a simulation model for disease spread over a given population and time interval.

Parameters:
params (Dict[str, Any]): Configuration parameters for the model.
path (str): File path or directory path for data access.
pop_geoid (pd.DataFrame): Geographical identifiers for the population.
index_dict (Dict[Any, Any]): Dictionary mapping indices for network construction.
net_type (str): Type of network used in the model.
date_interval (List[str]): List of dates over which the model is run.
model (str): Type of model to run, defaults to 'SEIR'.
num_sims (int): Number of simulations to run, defaults to 36.
initial_cond (Optional[pd.DataFrame]): Initial conditions for the model, optional.

Returns:
pd.DataFrame: A DataFrame containing the results of the simulations.
"""

• [ ] Actual executions, e.g. benchmarking speed and explaining applications, go in examples folder as a .ipynb
• [ ] create a requirements file in the repository

[GolanTrev]

This is one of the main deliverables we show Duncan. The actual asset.