assumptions

Signature/Parameters

def assumptions(self, category = None, verbose = False, assumption_type = None)

Retrieve identification assumptions grouped by category.

Parameters:

Name	Type	Description	Default
category	str or None	Filter assumptions to a specific category (e.g., 'identification'). When None (default), all available categories are returned.	None
verbose	bool	If True, include additional descriptive information when supported by the underlying identification object. Defaults to False.	False
assumption_type	str or None	Filter assumptions to 'causal' or 'statistical'.	None

Returns:

Type	Description
list[str] or None	Requested assumption definitions, or verbose assumption summaries when verbose=True. Returns None when filters are invalid.

Examples:

>>> G = DAG(graph="X -> Y")
>>> G.identification_analysis(exposure="X", outcome="Y", verbose=False)
>>> G.assumptions(category="identification")

Source code in causalinf/gcm.py

def assumptions(self, category=None, verbose=False, assumption_type=None):
    """
    Retrieve identification assumptions grouped by category.

    Parameters
    ----------
    category : str or None, optional
        Filter assumptions to a specific category (e.g., ``'identification'``).
        When ``None`` (default), all available categories are returned.
    verbose : bool, optional
        If ``True``, include additional descriptive information when supported
        by the underlying identification object. Defaults to ``False``.
    assumption_type : str or None, optional
        Filter assumptions to ``'causal'`` or ``'statistical'``.

    Returns
    -------
    list[str] or None
        Requested assumption definitions, or verbose assumption summaries
        when ``verbose=True``. Returns ``None`` when filters are invalid.

    Examples
    --------
    >>> G = DAG(graph="X -> Y")
    >>> G.identification_analysis(exposure="X", outcome="Y", verbose=False)
    >>> G.assumptions(category="identification")
    """
    if not self.__identification__:
        self.identification_analysis()
    return self.__identification__.assumptions(
        category=category, verbose=verbose, assumption_type=assumption_type
    )