滑块演示

使用滑块小部件来控制绘图的可视属性。

在此示例中，滑块用于选择正弦波的频率。 您可以通过这种方式控制绘图的许多连续变化属性。

滑块演示

  1. import numpy as np
  2. import matplotlib.pyplot as plt
  3. from matplotlib.widgets import Slider, Button, RadioButtons
  5. fig, ax = plt.subplots()
  6. plt.subplots_adjust(left=0.25, bottom=0.25)
  7. t = np.arange(0.0, 1.0, 0.001)
  8. a0 = 5
  9. f0 = 3
  10. delta_f = 5.0
  11. s = a0*np.sin(2*np.pi*f0*t)
  12. l, = plt.plot(t, s, lw=2, color='red')
  13. plt.axis([0, 1, -10, 10])
  15. axcolor = 'lightgoldenrodyellow'
  16. axfreq = plt.axes([0.25, 0.1, 0.65, 0.03], facecolor=axcolor)
  17. axamp = plt.axes([0.25, 0.15, 0.65, 0.03], facecolor=axcolor)
  19. sfreq = Slider(axfreq, 'Freq', 0.1, 30.0, valinit=f0, valstep=delta_f)
  20. samp = Slider(axamp, 'Amp', 0.1, 10.0, valinit=a0)
  23. def update(val):
  24.     amp = samp.val
  25.     freq = sfreq.val
  26.     l.set_ydata(amp*np.sin(2*np.pi*freq*t))
  27.     fig.canvas.draw_idle()
  28. sfreq.on_changed(update)
  29. samp.on_changed(update)
  31. resetax = plt.axes([0.8, 0.025, 0.1, 0.04])
  32. button = Button(resetax, 'Reset', color=axcolor, hovercolor='0.975')
  35. def reset(event):
  36.     sfreq.reset()
  37.     samp.reset()
  38. button.on_clicked(reset)
  40. rax = plt.axes([0.025, 0.5, 0.15, 0.15], facecolor=axcolor)
  41. radio = RadioButtons(rax, ('red', 'blue', 'green'), active=0)
  44. def colorfunc(label):
  45.     l.set_color(label)
  46.     fig.canvas.draw_idle()
  47. radio.on_clicked(colorfunc)
  49. plt.show()

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