Class vectorize

numpy/lib/function_base.py:2118–2522

vectorize(pyfunc=np._NoValue, otypes=None, doc=None, excluded=None, cache=False, signature=None) Returns an object that acts like pyfunc, but takes arrays as input. Define a vectorized function which takes a nested sequence of objects or numpy arrays as inputs and returns a si

@set_module('numpy')
class vectorize:
    """
    vectorize(pyfunc=np._NoValue, otypes=None, doc=None, excluded=None,
    cache=False, signature=None)

    Returns an object that acts like pyfunc, but takes arrays as input.

    Define a vectorized function which takes a nested sequence of objects or
    numpy arrays as inputs and returns a single numpy array or a tuple of numpy
    arrays. The vectorized function evaluates `pyfunc` over successive tuples
    of the input arrays like the python map function, except it uses the
    broadcasting rules of numpy.

    The data type of the output of `vectorized` is determined by calling
    the function with the first element of the input.  This can be avoided
    by specifying the `otypes` argument.

    Parameters
    ----------
    pyfunc : callable, optional
        A python function or method.
        Can be omitted to produce a decorator with keyword arguments.
    otypes : str or list of dtypes, optional
        The output data type. It must be specified as either a string of
        typecode characters or a list of data type specifiers. There should
        be one data type specifier for each output.
    doc : str, optional
        The docstring for the function. If None, the docstring will be the
        ``pyfunc.__doc__``.
    excluded : set, optional
        Set of strings or integers representing the positional or keyword
        arguments for which the function will not be vectorized.  These will be
        passed directly to `pyfunc` unmodified.

        .. versionadded:: 1.7.0

    cache : bool, optional
        If `True`, then cache the first function call that determines the number
        of outputs if `otypes` is not provided.

        .. versionadded:: 1.7.0

    signature : string, optional
        Generalized universal function signature, e.g., ``(m,n),(n)->(m)`` for
        vectorized matrix-vector multiplication. If provided, ``pyfunc`` will
        be called with (and expected to return) arrays with shapes given by the
        size of corresponding core dimensions. By default, ``pyfunc`` is
        assumed to take scalars as input and output.

        .. versionadded:: 1.12.0

    Returns
    -------
    out : callable
        A vectorized function if ``pyfunc`` was provided,
        a decorator otherwise.

    See Also