Question

我正在处理ML项目，并且希望实时（相对）显示具有适应度函数的图表。

我正在使用this SO answer中的代码，只要该图表显示在matplotlib窗口中，它就可以正常工作。只要将其添加到页面中，它就会变成静态图像。

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

fig, ax = plt.subplots()

max_x = 5
max_rand = 10

x = np.arange(0, max_x)
ax.set_ylim(0, max_rand)
line, = ax.plot(x, np.random.randint(0, max_rand, max_x))


def init():  # give a clean slate to start
    line.set_ydata([np.nan] * len(x))
    return line,


def animate(i):  # update the y values (every 1000ms)
    line.set_ydata(np.random.randint(0, max_rand, max_x))
    return line,

ani = animation.FuncAnimation(
    fig, animate, init_func=init, interval=1000, blit=True, save_count=10)

st.pyplot(plt)

任何想法如何为图表设置动画？不必是matplotlib。

Answer 1

我收到了answer on the streamlit forum，所以我只是在这里复制更新的代码

import matplotlib.pyplot as plt
import numpy as np
import streamlit as st
import time

fig, ax = plt.subplots()

max_x = 5
max_rand = 10

x = np.arange(0, max_x)
ax.set_ylim(0, max_rand)
line, = ax.plot(x, np.random.randint(0, max_rand, max_x))
the_plot = st.pyplot(plt)

def init():  # give a clean slate to start
    line.set_ydata([np.nan] * len(x))

def animate(i):  # update the y values (every 1000ms)
    line.set_ydata(np.random.randint(0, max_rand, max_x))
    the_plot.pyplot(plt)

init()
for i in range(100):
    animate(i)
    time.sleep(0.1)

如何在流线型页面中为折线图制作动画

1 个答案: