Matplotlib 滑塊 - y 軸的自動縮放

Question

為簡單起見，請考慮以下函數：f(x) = A * sin(w * x)。 我使用滑塊查看更改這兩個參數的影響，代碼運行良好，但是我遇到了問題。 如果振幅 A 太大，則畫布中不再有函數的最大值（請參閱結果情況的圖片）...我嘗試了一些天真的可能性（請參閱下面的代碼）：最初定義 y 限制並更新它們與函數本身同時發生，但只有函數的大小發生變化，y 軸沒有任何變化......

from matplotlib import pyplot as plt
from matplotlib.widgets import Slider, Button
import numpy as np

## Slider parameters 

w_init = 1  # Initial value for slider 
w_min = 1   # Minimum value of slider
w_max = 10   # Maximum value of slider

A_init = 1  # Initial value for slider 
A_min = 1   # Minimum value of slider
A_max = 10   # Maximum value of slider


## Calculation
x = np.arange(0,10,0.1)
f =A_init * np.sin(w_init*x)

## Plot & Slider

fig, ax = plt.subplots()
plt.subplots_adjust(left=0.15, bottom=0.3)
tot_plot, = plt.plot(x,f, 'b')
plt.ylim(-A_init,A_init)


# Creates the axes for each slider
slidercolor = "blue"
w_slider_axe = plt.axes([0.15, 0.17, 0.7, 0.02])
A_slider_axe = plt.axes([0.15, 0.11, 0.7, 0.02])

# Creates the slider
w_slider = Slider(w_slider_axe, "w", w_min, w_max, valinit = w_init, valfmt="%.1E", color=slidercolor)
A_slider = Slider(A_slider_axe, "A", A_min, A_max, valinit = A_init, valfmt="%.1E", color=slidercolor)

# This function updates all the values of the function and draws the plot again
def update(val):
    f = A_slider.val * np.sin(w_slider.val * x)
    tot_plot.set_ydata(f)
    fig.canvas.draw_idle()
    plt.ylim(-A_slider.val,A_slider.val)

w_slider.on_changed(update)
A_slider.on_changed(update)
plt.show()

有人知道如何解決嗎？ 對不起，我只是個新手;)。 謝謝

Answer 1

以下是在 pyplot 中動態更改軸范圍的示例：

import matplotlib.pyplot as plt
import time
import random

x = range(0, 10, 1)
y = range(-50, 50, 10)

xdata = []
ydata = []

plt.show()
plt.plot(x, y)

plt.axis([0, 200, 0, 200])

plt.show()

Answer 2

我已經解決了“問題”。 這確實是一個細節，但對於像我這樣的新手來說，這並不明顯。 這是運行良好的代碼：

from matplotlib import pyplot as plt
from matplotlib.widgets import Slider, Button
import numpy as np

## Slider parameters 

w_init = 1  # Initial value for slider 
w_min = 1   # Minimum value of slider
w_max = 10   # Maximum value of slider

A_init = 1  # Initial value for slider 
A_min = 1   # Minimum value of slider
A_max = 10   # Maximum value of slider


## Calculation
x = np.arange(0,10,0.1)
f =A_init * np.sin(w_init*x)

## Plot & Slider

fig, ax = plt.subplots()
plt.subplots_adjust(left=0.15, bottom=0.3)
tot_plot, = plt.plot(x,f, 'b')
ax.set_ylim(-A_init,A_init)


# Creates the axes for each slider
slidercolor = "blue"
w_slider_axe = plt.axes([0.15, 0.17, 0.7, 0.02])
A_slider_axe = plt.axes([0.15, 0.11, 0.7, 0.02])

# Creates the slider
w_slider = Slider(w_slider_axe, "w", w_min, w_max, valinit = w_init, valfmt="%.1E", color=slidercolor)
A_slider = Slider(A_slider_axe, "A", A_min, A_max, valinit = A_init, valfmt="%.1E", color=slidercolor)

# This function updates all the values of the function and draws the plot again
def update(val):
    f = A_slider.val * np.sin(w_slider.val * x)
    tot_plot.set_ydata(f)
    fig.canvas.draw_idle()
    ax.set_ylim(-A_slider.val,A_slider.val)

w_slider.on_changed(update)
A_slider.on_changed(update)
plt.show()