Pandas 在圆内设置文本动画-Matplotlib

下面将基于给定半径设置圆和线的动画。我希望将情节与动画文本结合起来，突出显示圆圈内的不同部分。文本会为每个新帧更新，但不会删除以前的帧文本

注意：我试图保持动画功能，因为我希望轴保持不变，并且只为更新的数据设置动画

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

df = pd.DataFrame({   
    'Time' : [1,1,1,1,2,2,2,2,3,3,3,3],                        
    '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],    
    'Angle' : [0,0,0,0,-45,-45,-45,-45,90,90,90,90],                    
    })

fig = plt.figure(figsize = (8,10))

grid = gridspec.GridSpec(1, 2)
gridsize = (1, 2)

ax = plt.subplot2grid(gridsize, (0, 0))
ax2 = plt.subplot2grid(gridsize, (0, 1))
ax2.set_xlim(-10, 10)
ax2.set_ylim(-10, 10)

# 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))
moving_point = ax.scatter(moving_x[0], moving_y[0], c = 'black', marker = 'o', zorder = 3)

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

circle = plt.Circle(radius[0], 10, color = 'black', fill = False, lw = 0.2)
circle2 = plt.Circle(radius[0], 10, color = 'red', fill = False, lw = 0.2)

ax.add_patch(circle)
ax2.add_patch(circle2)

line1, = ax.plot([],[], color = 'k', linewidth = 1)
line2, = ax.plot([],[], color = 'k', linewidth = 1)

t = df['Angle'][0]
angles = np.array(df.groupby(['Time'])['Angle'].apply(list))

angleText = df.drop_duplicates(subset = ['Time','Angle'])['Angle'].values

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))]
])

# compass tags
annotate_tags = ['N','E','S','W']

def animate(i) :

    moving_point.set_offsets(np.c_[moving_x[0+i], moving_y[0+i]])
    circle.center = (radius[i,0], radius[i,1])

    xs1L1=-10.0/2**0.5
    ys1L1=10.0/2**0.5
    xs2L1=10.0/2**0.5
    ys2L1=-10.0/2**0.5

    xs1L2=-xs1L1
    ys1L2=ys1L1
    xs2L2=-xs1L2
    ys2L2=ys2L1

    cx=radius[i,0]
    cy=radius[i,1]

    theta=math.radians(angles[i][0])

    x1L1=(  (xs1L1+radius[i,0] - cx) * math.cos(theta) + (ys1L1+radius[i,1] - cy) * math.sin(theta) ) + cx
    x2L1=(  (xs2L1+radius[i,0] - cx) * math.cos(theta) + (ys2L1+radius[i,1]- cy) * math.sin(theta) ) + cx
    y1L1=( -(xs1L1+radius[i,0] - cx) * math.sin(theta) + (ys1L1+radius[i,1] - cy) * math.cos(theta) ) + cy
    y2L1=( -(xs2L1+radius[i,0] - cx) * math.sin(theta) + (ys2L1+radius[i,1] - cy) * math.cos(theta) ) + cy

    line1.set_data([x1L1,x2L1],[y1L1,y2L1])

    x1L2=(  (xs1L2+radius[i,0] - cx) * math.cos(theta) + (ys1L2+radius[i,1] - cy) * math.sin(theta) ) + cx
    x2L2=(  (xs2L2+radius[i,0] - cx) * math.cos(theta) + (ys2L2+radius[i,1]- cy) * math.sin(theta) ) + cx
    y1L2=( -(xs1L2+radius[i,0] - cx) * math.sin(theta) + (ys1L2+radius[i,1] - cy) * math.cos(theta) ) + cy
    y2L2=( -(xs2L2+radius[i,0] - cx) * math.sin(theta) + (ys2L2+radius[i,1] - cy) * math.cos(theta) ) + cy

    line2.set_data([x1L2,x2L2],[y1L2,y2L2])        

    # Animate compass tags for each frame
    tag_pos = np.array([[0,8.5],[8.5,0],[0,-8.5],[-8.5,0]])    
    tag_pos = tag_pos @ rot_mat(angleText[i])

    for tag,pos in zip(annotate_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)

---

您希望为

动画

功能之外的尽可能多的标记创建文本对象。在

animate

函数

set_text

和

set_position

中，如下所示：

---

我建议您在动画功能之外使用

annotate

创建文本对象。然后，您可以在

animate

函数中的那些文本对象上

.set_x（）

和

.set_y（）

，类似于对行使用

.set_data（）

的方式。

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

df = pd.DataFrame({   
    'Time' : [1,1,1,1,2,2,2,2,3,3,3,3],                        
    '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],    
    'Angle' : [0,0,0,0,-45,-45,-45,-45,90,90,90,90],                    
    })

fig = plt.figure(figsize = (20,10))

grid = gridspec.GridSpec(1, 2)
gridsize = (1, 2)

ax = plt.subplot2grid(gridsize, (0, 0))
ax2 = plt.subplot2grid(gridsize, (0, 1))
ax2.set_xlim(-10, 10)
ax2.set_ylim(-10, 10)

# 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))
moving_point = ax.scatter(moving_x[0], moving_y[0], c = 'black', marker = 'o', zorder = 3)

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

circle = plt.Circle(radius[0], 10, color = 'black', fill = False, lw = 0.2)
circle2 = plt.Circle(radius[0], 10, color = 'red', fill = False, lw = 0.2)

ax.add_patch(circle)
ax2.add_patch(circle2)

line1, = ax.plot([],[], color = 'k', linewidth = 1)
line2, = ax.plot([],[], color = 'k', linewidth = 1)

t = df['Angle'][0]
angles = np.array(df.groupby(['Time'])['Angle'].apply(list))

angleText = df.drop_duplicates(subset = ['Time','Angle'])['Angle'].values

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))]
])

# compass tags
annotate_tags = ['N','E','S','W']
annotation=[None]*len(annotate_tags)
for i in range(len(annotate_tags)):
    annotation[i] = ax.annotate('', xy=(0, 0),xycoords='data',fontsize=10,horizontalalignment='right', verticalalignment='bottom')


def animate(i) :

    moving_point.set_offsets(np.c_[moving_x[0+i], moving_y[0+i]])
    circle.center = (radius[i,0], radius[i,1])

    xs1L1=-10.0/2**0.5
    ys1L1=10.0/2**0.5
    xs2L1=10.0/2**0.5
    ys2L1=-10.0/2**0.5

    xs1L2=-xs1L1
    ys1L2=ys1L1
    xs2L2=-xs1L2
    ys2L2=ys2L1

    cx=radius[i,0]
    cy=radius[i,1]

    theta=math.radians(angles[i][0])

    x1L1=(  (xs1L1+radius[i,0] - cx) * math.cos(theta) + (ys1L1+radius[i,1] - cy) * math.sin(theta) ) + cx
    x2L1=(  (xs2L1+radius[i,0] - cx) * math.cos(theta) + (ys2L1+radius[i,1]- cy) * math.sin(theta) ) + cx
    y1L1=( -(xs1L1+radius[i,0] - cx) * math.sin(theta) + (ys1L1+radius[i,1] - cy) * math.cos(theta) ) + cy
    y2L1=( -(xs2L1+radius[i,0] - cx) * math.sin(theta) + (ys2L1+radius[i,1] - cy) * math.cos(theta) ) + cy

    line1.set_data([x1L1,x2L1],[y1L1,y2L1])

    x1L2=(  (xs1L2+radius[i,0] - cx) * math.cos(theta) + (ys1L2+radius[i,1] - cy) * math.sin(theta) ) + cx
    x2L2=(  (xs2L2+radius[i,0] - cx) * math.cos(theta) + (ys2L2+radius[i,1]- cy) * math.sin(theta) ) + cx
    y1L2=( -(xs1L2+radius[i,0] - cx) * math.sin(theta) + (ys1L2+radius[i,1] - cy) * math.cos(theta) ) + cy
    y2L2=( -(xs2L2+radius[i,0] - cx) * math.sin(theta) + (ys2L2+radius[i,1] - cy) * math.cos(theta) ) + cy

    line2.set_data([x1L2,x2L2],[y1L2,y2L2])        

    # Animate compass tags for each frame
    tag_pos = np.array([[0,8.5],[8.5,0],[0,-8.5],[-8.5,0]])    
    tag_pos = tag_pos @ rot_mat(angleText[i])
    k=0
    for tag,pos in zip(annotate_tags,tag_pos):
        annotation[k].set_text(tag)
        annotation[k].set_position(xy=pos+radius[i])
        k=k+1

ani = animation.FuncAnimation(fig, animate, np.arange(0,3), blit = False)
ani.save('test.gif', writer='imagemagick', fps=5)
plt.show()