matplotlib–slider widget
哎哎哎:# t0]https://www . geeksforgeeks . org/matplotlib-slider widget/
Matplotlib 提供了几个小部件来制作交互图。在这些小部件中,这里讨论了滑块小部件。滑块提供对绘图视觉属性的控制。滑块()用于将表示绘图中浮点范围的滑块放置在提供的轴上。
语法:
class matplotlib . widgets . slider(ax,label,valmin,valmax,valinit = 0.5,valfmt=None,closedmin=True,closedmax=True,slidermin=None,slidermax=None,拖动=True,valstep=None,方向= '水平',kwargs)
参数:
- 轴:放置滑块的 matplotlib.axes.Axes 实例
- 标签:滑块文本标签
- valmin: 滑块的最小值
- 最大值:滑块的最大值
- 数值:滑块的初始值。默认值为 0.5。
- valfmt: 滑块值格式字符串(%)-格式。默认值为无。如果没有,则使用 ScalarFormatter 。
- closedmin: 滑块间隔是否在底部关闭。
- closedmax: 滑块间隔是否在顶部关闭。
- slidermin: 禁止当前滑块的值小于给定滑块的当前值。默认值为无。
- slidermax: 禁止当前滑块的值大于给定滑块的当前值。默认值为无。
- 拖动:滑块可以用鼠标拖动,也可以不用鼠标拖动。默认值为真(可以用鼠标拖动滑块)
- valstep: 滑块将以 valstep 值的倍数滑动。默认值为无。
- 方向:滑块方向,垂直或水平。默认值为水平。
- kwargs 与绘制滑块旋钮的矩形相关。有效属性,如面颜色、边缘颜色、alpha、等。这里可以使用矩形。
方法:
- 断开(自身,cid): 移除连接 id 为 cid 的观察器
- on_changed(self,func): 连接到滑块事件。当滑块值改变时,调用相应的功能功能。函数取一个新的滑块值作为参数,返回连接 id。
- 复位(自):滑块值设置为初始值
- set_val(self,val): 将滑块值设置为值
例 1:
以下示例演示了使用 reg、绿色和蓝色值滑块改变条形图的颜色。
Python 3
# Import libraries
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button
# Create a subplot
fig, ax = plt.subplots()
plt.subplots_adjust(bottom=0.35)
r = 0.6
g = 0.2
b = 0.5
# Create and plot a bar chart
year = ['2002', '2004', '2006', '2008', '2010']
production = [25, 15, 35, 30, 10]
plt.bar(year, production, color=(r, g, b),
edgecolor="black")
# Create 3 axes for 3 sliders red,green and blue
axred = plt.axes([0.25, 0.2, 0.65, 0.03])
axgreen = plt.axes([0.25, 0.15, 0.65, 0.03])
axblue = plt.axes([0.25, 0.1, 0.65, 0.03])
# Create a slider from 0.0 to 1.0 in axes axred
# with 0.6 as initial value.
red = Slider(axred, 'Red', 0.0, 1.0, 0.6)
# Create a slider from 0.0 to 1.0 in axes axgreen
# with 0.2 as initial value.
green = Slider(axgreen, 'Green', 0.0, 1.0, 0.2)
# Create a slider from 0.0 to 1.0 in axes axblue
# with 0.5(default) as initial value
blue = Slider(axblue, 'Blue', 0.0, 1.0)
# Create fuction to be called when slider value is changed
def update(val):
r = red.val
g = green.val
b = blue.val
ax.bar(year, production, color=(r, g, b),
edgecolor="black")
# Call update function when slider value is changed
red.on_changed(update)
green.on_changed(update)
blue.on_changed(update)
# Create axes for reset button and create button
resetax = plt.axes([0.8, 0.025, 0.1, 0.04])
button = Button(resetax, 'Reset', color='gold',
hovercolor='skyblue')
# Create a function resetSlider to set slider to
# initial values when Reset button is clicked
def resetSlider(event):
red.reset()
green.reset()
blue.reset()
# Call resetSlider function when clicked on reset button
button.on_clicked(resetSlider)
# Display graph
plt.show()
输出:
例 2:
在本例中,滑块用于改变正弦波的频率和振幅
Python 3
# Import libraries
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.widgets import Slider, Button
# Create subplot
fig, ax = plt.subplots()
plt.subplots_adjust(bottom=0.35)
# Create and plot sine wave
t = np.arange(0.0, 1.0, 0.001)
s = 5 * np.sin(2 * np.pi * 3 * t)
l, = plt.plot(t, s)
# Create axes for frequency and amplitude sliders
axfreq = plt.axes([0.25, 0.15, 0.65, 0.03])
axamplitude = plt.axes([0.25, 0.1, 0.65, 0.03])
# Create a slider from 0.0 to 20.0 in axes axfreq
# with 3 as initial value
freq = Slider(axfreq, 'Frequency', 0.0, 20.0, 3)
# Create a slider from 0.0 to 10.0 in axes axfreq
# with 5 as initial value and valsteps of 1.0
amplitude = Slider(axamplitude, 'Amplitude', 0.0,
10.0, 5, valstep=1.0)
# Create fuction to be called when slider value is changed
def update(val):
f = freq.val
a = amplitude.val
l.set_ydata(a*np.sin(2*np.pi*f*t))
# Call update function when slider value is changed
freq.on_changed(update)
amplitude.on_changed(update)
# display graph
plt.show()
输出:
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