Module « scipy.optimize »

Fonction rosen - module scipy.optimize

Signature de la fonction rosen

def rosen(x) 

Description

rosen.__doc__

    The Rosenbrock function.

    The function computed is::

        sum(100.0*(x[1:] - x[:-1]**2.0)**2.0 + (1 - x[:-1])**2.0)

    Parameters
    ----------
    x : array_like
        1-D array of points at which the Rosenbrock function is to be computed.

    Returns
    -------
    f : float
        The value of the Rosenbrock function.

    See Also
    --------
    rosen_der, rosen_hess, rosen_hess_prod

    Examples
    --------
    >>> from scipy.optimize import rosen
    >>> X = 0.1 * np.arange(10)
    >>> rosen(X)
    76.56

    For higher-dimensional input ``rosen`` broadcasts.
    In the following example, we use this to plot a 2D landscape.
    Note that ``rosen_hess`` does not broadcast in this manner.

    >>> import matplotlib.pyplot as plt
    >>> from mpl_toolkits.mplot3d import Axes3D
    >>> x = np.linspace(-1, 1, 50)
    >>> X, Y = np.meshgrid(x, x)
    >>> ax = plt.subplot(111, projection='3d')
    >>> ax.plot_surface(X, Y, rosen([X, Y]))
    >>> plt.show()