goldhunt_pass5.py 文件源码

def generate_random_points(ref_radius, total_points):
    """Return x, y coordinate lists representing random points inside a circle.

    This function illustrates NumPy capabilities. It is used in the
    optimization pass 4, 5, 6 in the chapter on performance of the book
    Learning Python  Application Development (Packt Publishing).

    The run time performance of this function will be
    significantly faster compared to the previous optimization pass.

    Generates random points inside a circle with center at (0,0). For any
    point, it randomly picks a radius between 0 and ref_radius.

    :param ref_radius: The random point lies between 0 and this radius.
    :param total_points: total number of random points to be created
    :return: x and y coordinates as lists

    .. todo:: Refactor! Move the function to a module like gameutilities.py
    """
    # Combination of avoiding the dots (function reevaluations)
    # and using local variable. This is similar to the
    # optimization pass-3 but here we use equivalent NumPy functions.
    l_uniform = np.random.uniform
    l_sqrt = np.sqrt
    l_pi = np.pi
    l_cos = np.cos
    l_sin = np.sin

    # Note that the variables theta and radius are now NumPy arrays.
    theta = l_uniform(0.0, 2.0*l_pi, total_points)
    radius = ref_radius*l_sqrt(l_uniform(0.0, 1.0, total_points))
    x = radius*l_cos(theta)
    y = radius*l_sin(theta)

    # Unlike optimization pass-4 (which returns x and y as Python lists,
    # here it returns the NumPy arrays directly to be consumed by
    # the GoldHunt.find_coins method
    return x, y