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Méthode numpy.random.RandomState.random_sample

Signature de la méthode random_sample

Description

random_sample.__doc__

        random_sample(size=None)

        Return random floats in the half-open interval [0.0, 1.0).

        Results are from the "continuous uniform" distribution over the
        stated interval.  To sample :math:`Unif[a, b), b > a` multiply
        the output of `random_sample` by `(b-a)` and add `a`::

          (b - a) * random_sample() + a

        .. note::
            New code should use the ``random`` method of a ``default_rng()``
            instance instead; please see the :ref:`random-quick-start`.

        Parameters
        ----------
        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.

        Returns
        -------
        out : float or ndarray of floats
            Array of random floats of shape `size` (unless ``size=None``, in which
            case a single float is returned).

        See Also
        --------
        Generator.random: which should be used for new code.

        Examples
        --------
        >>> np.random.random_sample()
        0.47108547995356098 # random
        >>> type(np.random.random_sample())
        <class 'float'>
        >>> np.random.random_sample((5,))
        array([ 0.30220482,  0.86820401,  0.1654503 ,  0.11659149,  0.54323428]) # random

        Three-by-two array of random numbers from [-5, 0):

        >>> 5 * np.random.random_sample((3, 2)) - 5
        array([[-3.99149989, -0.52338984], # random
               [-2.99091858, -0.79479508],
               [-1.23204345, -1.75224494]])