如何使matplotlib根据数据范围更新我的轴

Question

我有一个实时动画，我想在每次重画时更新x和y轴。

我尝试了多种方法来解决这个问题，这些方法作为注释留在下面的代码中

我现在相信问题来自于返回行，它与变量ax有关，而FuncAnimation作用于变量fig？

import pandas as pd
import time
import matplotlib.pyplot as plt
import matplotlib.animation as animation
global df
df = pd.DataFrame(columns = ['time', 'number'])
global start_time
start_time = time.time()
df['time'] = [1]*40
df['number'] = [1]*40
global counter
counter = 0
while counter<40:
df.iat[counter, 0] = round(((time.time()-start_time)*10))
df.iat[counter, 1] = counter
time.sleep(0.1)
counter = counter+1
def get_data():
global counter
global start_time
global df
df.drop(range(10), axis = 0, inplace=True)
df2 = pd.DataFrame(columns = ['time', 'number'])
list1 = []
list2 = []
for item in range(10):
time.sleep(0.1)
list1.append(round(((time.time()-start_time)*10)))
list2.append(counter)
counter = counter + 1
df2['time'] = list1
df2['number'] = list2
df = df.append(df2, ignore_index = True)
df.reset_index(inplace=True, drop = True)
x_data = df['time']
y_data = df['number']
return x_data,y_data
def get_limits():
global df
x_min = min(df['time'])
y_min = min(df['number'])
x_max = max(df['time'])
y_max = max(df['number'])
return x_min, y_min, x_max, y_max
fig, ax = plt.subplots()
def animate(i):
x_data, y_data= get_data()
x_min, y_min, x_max, y_max = get_limits()
#plt.xlim(x_min, x_max, auto = True)
#plt.ylim(y_min, y_max, auto = True)
ax.set_xlim(x_min, x_max, auto = True)
ax.set_ylim(y_min, y_max, auto = True)
line = ax.plot(x_data, y_data)
#line = ax.plot(x_data, y_data,scalex=True, scaley=True, color="red")
#plt.plot(x,y, scaley=True, scalex=True, color="red")
return line
ani = animation.FuncAnimation(
fig, animate, interval=50, blit=True, save_count=50)
#ani2 = animation.FuncAnimation(ax, animate, interval = 50, blit=True, save_count=50)
plt.show()

Answer 1

我能够通过下面的代码使轴动态更改。

关键的区别在于，我使用了plt.ylim和plt.xlim，而不是更改图形xlim或ylim。然而，它的Ive还在这些代码旁边添加了注释代码，这些代码也有效。我相信ax1是一个子图，它是分配给图的轴。因此，更新ax1，更新轴。这也可以通过fig.gca()访问，因为figure.gca()返回图形的轴

import pandas as pd
import time
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import random
global df
df = pd.DataFrame(columns = ['time', 'number'])
global start_time
start_time = time.time()
df['time'] = [1]*40
df['number'] = [1]*40
global counter
counter = 0
while counter<40:
df.iat[counter, 0] = round(((time.time()-start_time)*20))
df.iat[counter, 1] = counter
time.sleep(0.05)
counter = counter+1
def get_data():
global counter
global start_time
global df
df.drop(range(10), axis = 0, inplace=True)
df2 = pd.DataFrame(columns = ['time', 'number'])
list1 = []
list2 = []
for item in range(10):
time.sleep(random.randint(10,100)/1000)
list1.append(round(((time.time()-start_time)*20)))
list2.append(counter)
counter = counter + 1
df2['time'] = list1
df2['number'] = list2
df = df.append(df2, ignore_index = True)
df.reset_index(inplace=True, drop = True)
x_data = df['time']
y_data = df['number']
return x_data,y_data
def get_limits():
global df
x_min = min(df['time'])
y_min = min(df['number'])
x_max = max(df['time'])
y_max = max(df['number'])
return x_min, y_min, x_max, y_max
fig = plt.figure(figsize = (18,9))
ax1 = fig.add_subplot(1,1,1)
plt.title("Dynamic Axes")
def animate(i):
x_data, y_data = get_data()
x_min, y_min, x_max, y_max = get_limits()
plt.xlim(x_min, x_max) #ax1.set_ylim(y_min, y_max)
plt.ylim(y_min,y_max) #fig.gca().set_xlim(x_min,x_max)
plt.plot(x_data,y_data)
animation = animation.FuncAnimation(fig, animate, interval = 50)
plt.show()