python - 圆内的动画线 - matplotlib

Question

我正在尝试使用 matplotlib 制作线条动画。我可以为圆和一些散点设置动画，但我尝试使用变化的角度添加线条。使用下面的方法，我确定每个时间点的 X2、Y2 的方向，以确定方向。然后我想绘制显示该方向的线。他们基本上将圆分成 4 个相等的部分。我在下面单独插入了每个框架。我已输入指南针作为引用。

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import animation

fig, ax = plt.subplots(figsize = (8,8))
ax.set_xlim(-20,20)
ax.set_ylim(-20,20)
ax.grid(False)

df = pd.DataFrame({   
    'Time' : [1,1,1,1,2,2,2,2,3,3,3,3],             
    'id' : ['A','B','C','D','A','B','C','D','A','B','C','D'],                 
    'X1' : [1,8,0,-5,1,1,-6,0,1,8,0,-5],
    'Y1' : [-5,2,-5,2,5,-5,-2,2,-5,2,-5,2],
    'X2' : [0,0,0,0,-1,-1,-1,-1,0,0,0,0],
    'Y2' : [0,0,0,0,1,1,1,1,1,1,1,1],    
    'Rotation' : [0,0,0,0,-0.78,-0.78,-0.78,-0.78,1.57,1.57,1.57,1.57],
    'Angle' : [0,0,0,0,-45,-45,-45,-45,90,90,90,90],                    
    })

points_x = np.array(df.groupby(['Time'])['X1'].apply(list))
points_y = np.array(df.groupby(['Time'])['Y1'].apply(list))

# scatter points
points = ax.scatter(points_x[2], points_y[2], c = 'blue', marker = '*')

moving_x = np.array(df.groupby(['Time'])['X2'].apply(list))
moving_y = np.array(df.groupby(['Time'])['Y2'].apply(list))

# scatter moving
moving_point = ax.scatter(moving_x[2], moving_y[2], c = 'black', marker = 'x')

# Array of immediate congestion radius coordinates
radius = df.drop_duplicates(subset = ['Time','X2', 'Y2'])[['X2', 'Y2']].values

# Plot immediate congestion radius
circle = plt.Circle(radius[2], 10, color = 'black', fill = False)

# Add radius to plot
ax.add_patch(circle)

t = df['Angle'][0]
line1, = ax.plot([0, 0],[0,t], color = 'b', linewidth = 1)

def animate(i) :

    circle.center = (radius[i,0], radius[i,1])

    line1.set_data([i, i],[0,t])

    points.set_offsets(np.c_[points_x[0+i], points_y[0+i]])
    moving_point.set_offsets(np.c_[moving_x[0+i], moving_y[0+i]])


ani = animation.FuncAnimation(fig, animate,  np.arange(0,2), blit = False)

如果我将帧单独拆分，我希望它们显示以下内容:

帧 1:

帧 2:

第 3 帧:

编辑2:

Answer 1

为了处理您帖子中玩具数据集之外的数据集，我将创建动画的所有内容都放入函数 animate 中。由于我不熟悉您正在使用的数据集(例如，我不知道 Rotation 的作用)，因此下面的脚本是我能做的最好的。

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import animation

df = pd.DataFrame({   
    'Time' : [1,1,1,1,2,2,2,2,3,3,3,3],             
    'id' : ['A','B','C','D','A','B','C','D','A','B','C','D'],                 
    'X1' : [1,8,0,-5,1,1,-6,0,1,8,0,-5],
    'Y1' : [-5,2,-5,2,5,-5,-2,2,-5,2,-5,2],
    'X2' : [0,0,0,0,-1,-1,-1,-1,0,0,0,0],
    'Y2' : [0,0,0,0,1,1,1,1,1,1,1,1],    
    'Rotation' : [0,0,0,0,-0.78,-0.78,-0.78,-0.78,1.57,1.57,1.57,1.57],
    'Angle' : [0,0,0,0,-45,-45,-45,-45,90,90,90,90],                    
    })

# the scattered points in the compass
points_x = np.array(df.groupby(['Time'])['X1'].apply(list))
points_y = np.array(df.groupby(['Time'])['Y1'].apply(list))

# the center of the compass
moving_x = np.array(df.groupby(['Time'])['X2'].apply(list))
moving_y = np.array(df.groupby(['Time'])['Y2'].apply(list))

radius = df.drop_duplicates(subset = ['Time','X2', 'Y2'])[['X2', 'Y2']].values
angles = df['Angle'].unique()

rot_mat = lambda theta:np.array([
    [np.cos(np.deg2rad(theta)),-np.sin(np.deg2rad(theta))],
    [np.sin(np.deg2rad(theta)),np.cos(np.deg2rad(theta))]
])

fig, ax = plt.subplots(figsize = (8,8))

def animate(i) :
    
    ax.clear()
    ax.set_xlim(-20,20)
    ax.set_ylim(-20,20)
        
    points = ax.scatter(points_x[i]+radius[i][0], points_y[i]+radius[i][1], c = 'blue', marker = '*')
    moving_point = ax.scatter(moving_x[i],moving_y[i], c = 'black', marker = 'x')
    
    circle = plt.Circle(radius[i], 10, color = 'black', fill = False)
    ax.add_patch(circle)

    ends_one = np.array([[-7.07106781,7.07106781],[7.07106781,-7.07106781]])
    ends_two = np.array([[-7.07106781,-7.07106781],[7.07106781,7.07106781]])
    ends_one = ends_one @ rot_mat(angles[i]) + radius[i]
    ends_two = ends_two @ rot_mat(angles[i]) + radius[i]
    line1, = ax.plot([], [], ls='--', color='black',lw=1, zorder=10,animated=True)
    line2, = ax.plot([], [], ls='--', color='black',lw=1, zorder=10,animated=True)
    line1.set_data([ends_one[0][0],ends_one[1][0]],[ends_one[0][1],ends_one[1][1]])
    line2.set_data([ends_two[0][0],ends_two[1][0]],[ends_two[0][1],ends_two[1][1]])
    
    tags = ['N','E','S','W']
    tag_pos = np.array([[0,8.5],[8.5,0],[0,-8.5],[-8.5,0]])
    tag_pos = tag_pos @ rot_mat(angles[i])
    for tag,pos in zip(tags,tag_pos):
        ax.annotate(tag,xy=pos+radius[i], xycoords='data',
                    fontsize=10,horizontalalignment='right', verticalalignment='bottom')

ani = animation.FuncAnimation(fig, animate, np.arange(0,3), blit = False)
ani.save('test.gif', writer='pillow', fps=3)

如您所见，坐标可以迭代地传递到函数 animate 中以生成指南针的框架。运行此脚本后，您将获得一个 gif 文件 test.gif，可以预览该文件

---

删除过去帧的文本

有两种方法可以做到这一点

<强>1。如果您使用函数来创建动画

例如将 ax.clear() 放在函数的开头

import matplotlib.pyplot as plt
from matplotlib import animation

rot_mat = lambda theta:np.array([
    [np.cos(np.deg2rad(theta)),-np.sin(np.deg2rad(theta))],
    [np.sin(np.deg2rad(theta)),np.cos(np.deg2rad(theta))]
])

fig, ax = plt.subplots(figsize = (8,8))

centers = np.linspace(1,36,36).reshape(18,2)*0.2
angles = np.linspace(45,90,18)

def animate(i) :
    
    ax.clear()
    ax.set_xlim(-20,20)
    ax.set_ylim(-20,20)
            
    circle = plt.Circle(centers[i], 10, color = 'black', fill = True)
    circle.set_facecolor('violet')
    ax.add_patch(circle)

    tags = ['N','E','S','W']
    tag_pos = np.array([[0,8.5],[8.5,0],[0,-8.5],[-8.5,0]])
    tag_pos = tag_pos @ rot_mat(angles[i])
    for tag,pos in zip(tags,tag_pos):
        ax.annotate(tag,xy=pos+centers[i], xycoords='data',
                    fontsize=10,horizontalalignment='right', verticalalignment='bottom')

ani = animation.FuncAnimation(fig, animate, np.arange(0,18), blit = False)
ani.save('test.gif', writer='pillow', fps=18)

这将创建一个像这样的gif

<强>2。如果您不使用函数来创建动画

例如，您需要手动删除文本

import matplotlib.pyplot as plt
from matplotlib import animation

rot_mat = lambda theta:np.array([
    [np.cos(np.deg2rad(theta)),-np.sin(np.deg2rad(theta))],
    [np.sin(np.deg2rad(theta)),np.cos(np.deg2rad(theta))]
])

centers = np.linspace(1,36,36).reshape(18,2)*0.2
angles = np.linspace(45,90,18)

fig, ax = plt.subplots(figsize = (8,8))
ax.set_xlim(-20,20)
ax.set_ylim(-20,20)
    
circle = plt.Circle(centers[0], 10, color = 'black', fill = True)
circle.set_facecolor('violet')
ax.add_patch(circle)

annotates = []
tags = ['N','E','S','W']
tag_pos = np.array([[0,8.5],[8.5,0],[0,-8.5],[-8.5,0]])
tag_pos = tag_pos @ rot_mat(angles[0])
for tag,pos in zip(tags,tag_pos):
    ann = ax.annotate(tag,xy=pos+centers[0], xycoords='data',
                      fontsize=10,horizontalalignment='right', verticalalignment='bottom')
    annotates.append(ann)

for i in range(18):
    
    circle.center = centers[i]
    # remove the previous text
    for item in annotates: item.remove()
    annotates = []
    
    tag_pos = tag_pos @ rot_mat(angles[i])
    for tag,pos in zip(tags,tag_pos):
        ann = ax.annotate(tag,xy=pos+centers[i], xycoords='data',
                          fontsize=10,horizontalalignment='right', verticalalignment='bottom')
        annotates.append(ann)

ani = animation.FuncAnimation(fig, animate, np.arange(0,18), blit = False)
ani.save('test.gif', writer='pillow', fps=18)

如您所见，使用这行代码for item in annotates: item.remove()，前一帧的文本将被删除。因此，通过运行此脚本，您还将获得