无法为python matplotlib中的相同补丁的克隆制作动画 [英] Cannot animate clones of the same patch in python matplotlib

问题描述

我目前正在尝试进行模拟，其中多个粒子代理（蓝点）试图跟随敌方粒子（红点）。我设法使模拟使一个蓝点跟随红点，但是我在模拟中产生多个版本的蓝点（也试图使其显示在随机的初始位置）时遇到了麻烦跟随红点。

I am currently trying to make a simulation in which multiple particle agents (blue dots) try to follow the enemy particle (red dot). I have managed to get my simulation to have one blue dot follow the red dot, but I am having trouble producing multiple version of the blue dots (also trying ot get it to appear at random initial locations) in the simulation and animating all of them to follow the red dot.

有任何解决方法的想法吗？

Any ideas on how to fix this?

尝试为蓝色克隆制作动画粒子：

Attempt to animate clones of blue particles:

import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation
from matplotlib.collections import PatchCollection
from matplotlib import cm

import random

fig = plt.figure()
fig.set_dpi(100)
fig.set_size_inches(5, 4.5)

ax = plt.axes(xlim=(0, 100), ylim=(0, 100))
enemy = plt.Circle((10, -10), 0.75, fc='r')
agent = plt.Circle((10, -10), 0.75, fc='b')

p = None

def init():
    enemy.center = (5, 5)

    agent.center = (random.randint(1, 100), random.randint(1, 100))
    ax.add_patch(agent)

    for x in range(0,5):
        agent_clone = plt.Circle((10, -10), 0.75, fc='b')
        agent_clone.center = (random.randint(1, 100), random.randint(1, 100))
        patches_ac.append(agent_clone)


    p = PatchCollection(patches_ac, cmap=cm.prism, alpha=0.4)
    ax.add_collection(p)

    ax.add_patch(enemy)

    return []

def initalizePosition(agent,enemy):
    x_a, y_a = agent.center
    x_e, y_e = enemy.center

    x_a += 50
    y_a += 50

    agent.center = (x_a, y_a)
    enemy.center = (x_e, y_e)
    return agent    


def animationManage(i,agent,enemy):
    animateCos(i,enemy)
    #animateCirc(i,enemy)

    #animateLine(i,agent)
    followTarget(i,agent,enemy)

    return []

def followTarget(i, patch, enemy_patch):
    x, y = patch.center


    # Calculating velocity
    # v(t+1) = wv(t) + rand_1()c_1(p(t)  - x(t)) + rand_2()c_2(g(t) - x(t))
    v_x, v_y = velocity_calc(patch, enemy_patch)

    # Implementing:
    # x(t+1) = x(t) + v(t + 1)

    # x position
    x += v_x

    # y position
    y += v_y

    patch.center = (x, y)
    return patch,


def inertia_calc():
    return 0



def top_speed_regulate(curr_speed):
    top_speed = 0.5

    if curr_speed > top_speed:
        return top_speed
    elif curr_speed < -top_speed:
        return -top_speed
    else:
        return curr_speed

def velocity_calc(agent_patch, enemy_patch):

    x, y = agent_patch.center
    x_e, y_e = enemy_patch.center


    pos_vect = np.array([x,y], dtype='f')





    velo_vect = np.array([0.0,0.0], dtype='f')

    velo_vect[0] = top_speed_regulate( (x_e - x)* 0.05 )
    velo_vect[1] = top_speed_regulate( (y_e - y)* 0.05 )



    return velo_vect[0], velo_vect[1]


def animateLine(i, patch):
    x, y = patch.center

    x += 0.25
    y += 0.25
    patch.center = (x, y)
    return patch,


def animateCos(i, patch):
    x, y = patch.center

    x += 0.1
    #x += 0.4

    y = 50 + 30 * np.cos(np.radians(i))
    #y = 50 + 10 * np.cos(np.radians(i))
    patch.center = (x, y)
    return patch,


def animateCirc(i, patch):
    # It seems that i represents time step
    x, y = patch.center
    # 1st constant = position and 2nd constant = trajectory
    x = 50 + 30 * np.sin(np.radians(i))
    y = 50 + 30 * np.cos(np.radians(i))
    patch.center = (x, y)
    return patch,




anim = animation.FuncAnimation(fig, animationManage,
                               init_func=init,
                               frames=1000,
                               fargs=(agent,enemy,),
                               interval=1,
                               blit=True,
                               repeat=True)


plt.show()

只有一个蓝色的工作版本粒子：

Working version of the code with just one blue particle:

import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation

import random

fig = plt.figure()
fig.set_dpi(100)
fig.set_size_inches(5, 4.5)

ax = plt.axes(xlim=(0, 100), ylim=(0, 100))
enemy = plt.Circle((10, -10), 0.75, fc='r')
agent = plt.Circle((10, -10), 0.75, fc='b')



def init():
    enemy.center = (5, 5)

    agent.center = (random.randint(1, 100), random.randint(1, 100))
    ax.add_patch(agent)

    ax.add_patch(enemy)

    return []

def initalizePosition(agent,enemy):
    x_a, y_a = agent.center
    x_e, y_e = enemy.center

    x_a += 50
    y_a += 50

    agent.center = (x_a, y_a)
    enemy.center = (x_e, y_e)
    return agent    


def animationManage(i,agent,enemy):
    animateCos(i,enemy)
    #animateCirc(i,enemy)

    #animateLine(i,agent)
    followTarget(i,agent,enemy)

    return []

def followTarget(i, patch, enemy_patch):
    x, y = patch.center


    # Calculating velocity
    # v(t+1) = wv(t) + rand_1()c_1(p(t)  - x(t)) + rand_2()c_2(g(t) - x(t))
    v_x, v_y = velocity_calc(patch, enemy_patch)

    # Implementing:
    # x(t+1) = x(t) + v(t + 1)

    # x position
    x += v_x

    # y position
    y += v_y

    patch.center = (x, y)
    return patch,


def inertia_calc():
    return 0



def top_speed_regulate(curr_speed):
    top_speed = 0.5

    if curr_speed > top_speed:
        return top_speed
    elif curr_speed < -top_speed:
        return -top_speed
    else:
        return curr_speed

def velocity_calc(agent_patch, enemy_patch):

    x, y = agent_patch.center
    x_e, y_e = enemy_patch.center


    pos_vect = np.array([x,y], dtype='f')





    velo_vect = np.array([0.0,0.0], dtype='f')
    '''
    velo_vect[0] = top_speed_regulate( (x_e - x)* 0.05 )* random.random() 
    velo_vect[1] = top_speed_regulate( (y_e - y)* 0.05 )* random.random()
    '''

    velo_vect[0] = top_speed_regulate( (x_e - x)* 0.05 )
    velo_vect[1] = top_speed_regulate( (y_e - y)* 0.05 )



    return velo_vect[0], velo_vect[1]


def animateLine(i, patch):
    x, y = patch.center

    x += 0.25
    y += 0.25
    patch.center = (x, y)
    return patch,


def animateCos(i, patch):
    x, y = patch.center

    x += 0.1
    #x += 0.4

    y = 50 + 30 * np.cos(np.radians(i))
    #y = 50 + 10 * np.cos(np.radians(i))
    patch.center = (x, y)
    return patch,


def animateCirc(i, patch):
    # It seems that i represents time step
    x, y = patch.center
    # 1st constant = position and 2nd constant = trajectory
    x = 50 + 30 * np.sin(np.radians(i))
    y = 50 + 30 * np.cos(np.radians(i))
    patch.center = (x, y)
    return patch,




anim = animation.FuncAnimation(fig, animationManage,
                               init_func=init,
                               frames=1000,
                               fargs=(agent,enemy,),
                               interval=1,
                               blit=True,
                               repeat=True)


plt.show()

推荐答案

import numpy as np
from matplotlib import pyplot as plt
from matplotlib import animation

import random

fig = plt.figure()
fig.set_dpi(100)
fig.set_size_inches(5, 4.5)

ax = plt.axes(xlim=(0, 100), ylim=(0, 100))
enemy = plt.Circle((10, -10), 0.75, fc='r')
agent = plt.Circle((10, -10), 0.75, fc='b')
patches_ac = []
ax.add_patch(agent)

for x in range(0, 5):
    agent_clone = plt.Circle((10, -10), 0.75, fc='b')
    agent_clone.center = (random.randint(1, 100), random.randint(1, 100))
    patches_ac.append(agent_clone)
    ax.add_patch(agent_clone)

ax.add_patch(enemy)


def init():
    enemy.center = (5, 5)

    agent.center = (random.randint(1, 100), random.randint(1, 100))
    for ac in patches_ac:
        ac.center = (random.randint(1, 100), random.randint(1, 100))
    return []


def animationManage(i):
    animateCos(i, enemy)
    followTarget(i, agent, enemy)
    for ac in patches_ac:
        followTarget(i, ac, enemy)

    return []

def followTarget(i, patch, enemy_patch):
    x, y = patch.center
    v_x, v_y = velocity_calc(patch, enemy_patch)

    # x position
    x += v_x

    # y position
    y += v_y

    patch.center = (x, y)
    return patches_ac


def top_speed_regulate(curr_speed):
    top_speed = 0.5

    if curr_speed > top_speed:
        return top_speed
    elif curr_speed < -top_speed:
        return -top_speed
    else:
        return curr_speed


def velocity_calc(agent_patch, enemy_patch):

    x, y = agent_patch.center
    x_e, y_e = enemy_patch.center

    velo_vect = np.array([0.0, 0.0], dtype='f')

    velo_vect[0] = top_speed_regulate( (x_e - x)* 0.05 )
    velo_vect[1] = top_speed_regulate( (y_e - y)* 0.05 )

    return velo_vect[0], velo_vect[1]


def animateCos(i, patch):
    x, y = patch.center
    x += 0.1

    y = 50 + 30 * np.cos(np.radians(i))
    patch.center = (x, y)
    return patch,


anim = animation.FuncAnimation(fig, animationManage,
                               init_func=init,
                               frames=1000,
                               interval=1,
                               blit=True,
                               repeat=True)


plt.show()

这篇关于无法为python matplotlib中的相同补丁的克隆制作动画的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！