rosen — SciPy v1.15.2 Manual (original) (raw)

scipy.optimize.

scipy.optimize.rosen(x)[source]#

The Rosenbrock function.

The function computed is:

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

Parameters:

xarray_like

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

Returns:

ffloat

The value of the Rosenbrock function.

Examples

import numpy as np 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()