将动画添加到随机游走图 [Python]

Question

我编写了一个绘制随机游走的代码。生成了traj 不同的随机游走，每个随机游走由n 步骤组成。我想动画他们的动作。我该怎么做？
我的代码如下：

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

def random_walk_2D(n, traj = 1):

    for i in range(traj):

        skoki = np.array([[0, 1], [1, 0], [-1, 0], [0, -1]])
        losy = np.random.randint(4, size = n)

        temp = skoki[losy, :]

        x = np.array([[0, 0]])

        temp1 = np.concatenate((x, temp), axis = 0)

        traj = np.cumsum(temp1, axis = 0)

        plt.plot(traj[:, 0], traj[:, 1])
        plt.plot(traj[-1][0], traj[-1][1], 'ro') #the last point

    plt.show()

Answer 1

就目前而言，您可以一次性生成轨迹。我的意思是traj = np.cumsum(temp1, axis = 0) 中的traj 已经包含了从头到尾的所有“故事”。如果你想创建一个“实时”的动画，你不应该一次生成traj，而是迭代地绘制新的步骤。怎么办：

import numpy as np
import matplotlib.pyplot as plt

def real_time_random_walk_2D_NT(
    nb_steps, nb_trajs, with_dots=False, save_trajs=False, tpause=.01
    ):
    """
    Parameters
    ----------
    nb_steps     : integer
                   number of steps
    nb_trajs     : integer
                   number of trajectories
    save_trajs   : boolean (optional)
                   If True, entire trajectories are saved rather than
                   saving only the last steps needed for plotting.
                   False by default.
    with_dots    : boolean (optional)
                   If True, dots representative of random-walking entities
                   are displayed. Has precedence over `save_trajs`. 
                   False by default. 
    tpause       : float (optional)
                   Pausing time between 2 steps. .01 secondes by default.   
    """
    skoki = np.array([[0, 1], [1, 0], [-1, 0], [0, -1]])
    trajs = np.zeros((nb_trajs, 1, 2))
    for i in range(nb_steps):
        _steps = []
        for j in range(nb_trajs):
            traj = trajs[j,:,:]
            losy = np.random.randint(4, size = 1)
            temp = skoki[losy, :]
            traj = np.concatenate((traj, temp), axis = 0)
            traj[-1,:]   += traj[-2,:]
            _steps.append(traj)
        if save_trajs or with_dots:
            trajs = np.array(_steps)
            if with_dots:
                plt.cla()
                plt.plot(trajs[:,i, 0].T, trajs[:,i, 1].T, 'ro') ## There are leeway in avoiding these costly transpositions
                plt.plot(trajs[:,:i+1, 0].T, trajs[:,:i+1, 1].T)
            else:
                plt.plot(trajs[:,-1+i:i+1, 0].T, trajs[:,-1+i:i+1, 1].T)
        else:
            trajs = np.array(_steps)[:,-2:,:]
            plt.plot(trajs[:,:, 0].T, trajs[:,:, 1].T)

        plt.pause(tpause)


real_time_random_walk_2D_NT(50, 6, with_dots=True)

real_time_random_walk_2D_NT(50, 6)