Classe « Generator »

Méthode numpy.random.Generator.integers

Signature de la méthode integers

Description

integers.__doc__

        integers(low, high=None, size=None, dtype=np.int64, endpoint=False)

        Return random integers from `low` (inclusive) to `high` (exclusive), or
        if endpoint=True, `low` (inclusive) to `high` (inclusive). Replaces
        `RandomState.randint` (with endpoint=False) and
        `RandomState.random_integers` (with endpoint=True)

        Return random integers from the "discrete uniform" distribution of
        the specified dtype. If `high` is None (the default), then results are
        from 0 to `low`.

        Parameters
        ----------
        low : int or array-like of ints
            Lowest (signed) integers to be drawn from the distribution (unless
            ``high=None``, in which case this parameter is 0 and this value is
            used for `high`).
        high : int or array-like of ints, optional
            If provided, one above the largest (signed) integer to be drawn
            from the distribution (see above for behavior if ``high=None``).
            If array-like, must contain integer values
        size : int or tuple of ints, optional
            Output shape.  If the given shape is, e.g., ``(m, n, k)``, then
            ``m * n * k`` samples are drawn.  Default is None, in which case a
            single value is returned.
        dtype : dtype, optional
            Desired dtype of the result. Byteorder must be native.
            The default value is np.int64.
        endpoint : bool, optional
            If true, sample from the interval [low, high] instead of the
            default [low, high)
            Defaults to False

        Returns
        -------
        out : int or ndarray of ints
            `size`-shaped array of random integers from the appropriate
            distribution, or a single such random int if `size` not provided.

        Notes
        -----
        When using broadcasting with uint64 dtypes, the maximum value (2**64)
        cannot be represented as a standard integer type. The high array (or
        low if high is None) must have object dtype, e.g., array([2**64]).

        Examples
        --------
        >>> rng = np.random.default_rng()
        >>> rng.integers(2, size=10)
        array([1, 0, 0, 0, 1, 1, 0, 0, 1, 0])  # random
        >>> rng.integers(1, size=10)
        array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])

        Generate a 2 x 4 array of ints between 0 and 4, inclusive:

        >>> rng.integers(5, size=(2, 4))
        array([[4, 0, 2, 1],
               [3, 2, 2, 0]])  # random

        Generate a 1 x 3 array with 3 different upper bounds

        >>> rng.integers(1, [3, 5, 10])
        array([2, 2, 9])  # random

        Generate a 1 by 3 array with 3 different lower bounds

        >>> rng.integers([1, 5, 7], 10)
        array([9, 8, 7])  # random

        Generate a 2 by 4 array using broadcasting with dtype of uint8

        >>> rng.integers([1, 3, 5, 7], [[10], [20]], dtype=np.uint8)
        array([[ 8,  6,  9,  7],
               [ 1, 16,  9, 12]], dtype=uint8)  # random

        References
        ----------
        .. [1] Daniel Lemire., "Fast Random Integer Generation in an Interval",
               ACM Transactions on Modeling and Computer Simulation 29 (1), 2019,
               http://arxiv.org/abs/1805.10941.