如何在matplotlib中为colorbar设置动画

时间:2016-09-13 14:02:25

标签: python animation matplotlib colorbar

我有一个动画,其中数据的范围变化很​​大。我希望有colorbar跟踪数据的最大值和最小值(即我希望它不被修复)。问题是如何做到这一点。

理想情况下,我希望colorbar位于自己的轴上。

我尝试了以下四件事

1。天真的方法

问题:每个框架都有一个新的颜色条

#!/usr/bin/env python
"""
An animated image
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation

fig = plt.figure()
ax = fig.add_subplot(111)


def f(x, y):
    return np.exp(x) + np.sin(y)

x = np.linspace(0, 1, 120)
y = np.linspace(0, 2 * np.pi, 100).reshape(-1, 1)

frames = []

for i in range(10):
    x       += 1
    curVals  = f(x, y)
    vmax     = np.max(curVals)
    vmin     = np.min(curVals)
    levels   = np.linspace(vmin, vmax, 200, endpoint = True)
    frame    = ax.contourf(curVals, vmax=vmax, vmin=vmin, levels=levels)
    cbar     = fig.colorbar(frame)
    frames.append(frame.collections)

ani = animation.ArtistAnimation(fig, frames, blit=False)

plt.show()

2。添加到图像

将上面的for循环更改为

initFrame = ax.contourf(f(x,y)) 
cbar      = fig.colorbar(initFrame)
for i in range(10):
    x       += 1
    curVals  = f(x, y)
    vmax     = np.max(curVals)      
    vmin     = np.min(curVals)      
    levels   = np.linspace(vmin, vmax, 200, endpoint = True)
    frame    = ax.contourf(curVals, vmax=vmax, vmin=vmin, levels=levels)
    cbar.set_clim(vmin = vmin, vmax = vmax)
    cbar.draw_all()
    frames.append(frame.collections + [cbar])

问题:这引发了

AttributeError: 'Colorbar' object has no attribute 'set_visible'

3。在自己的轴上绘图

问题:colorbar未更新。

 #!/usr/bin/env python
 """
 An animated image
 """
 import numpy as np
 import matplotlib.pyplot as plt
 import matplotlib.animation as animation

 fig = plt.figure()
 ax1 = fig.add_subplot(121)
 ax2 = fig.add_subplot(122)


 def f(x, y):
     return np.exp(x) + np.sin(y)

 x = np.linspace(0, 1, 120)
 y = np.linspace(0, 2 * np.pi, 100).reshape(-1, 1)

 frames = []

 for i in range(10):
     x       += 1
     curVals  = f(x, y)
     vmax     = np.max(curVals)
     vmin     = np.min(curVals)
     levels   = np.linspace(vmin, vmax, 200, endpoint = True)
     frame    = ax1.contourf(curVals, vmax=vmax, vmin=vmin, levels=levels)
     cbar     = fig.colorbar(frame, cax=ax2) # Colorbar does not update
     frames.append(frame.collections)

 ani = animation.ArtistAnimation(fig, frames, blit=False)

 plt.show()

2.和4的组合。

问题:colorbar是常数。

类似的问题已发布here,但看起来OP对固定的colorbar感到满意。

1 个答案:

答案 0 :(得分:11)

虽然我不确定如何使用ArtistAnimation专门执行此操作,但使用FuncAnimation相当简单。如果我对您的"天真"进行以下修改版本1它的工作原理。

修改版本1

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from mpl_toolkits.axes_grid1 import make_axes_locatable

fig = plt.figure()
ax = fig.add_subplot(111)

# I like to position my colorbars this way, but you don't have to
div = make_axes_locatable(ax)
cax = div.append_axes('right', '5%', '5%')

def f(x, y):
    return np.exp(x) + np.sin(y)

x = np.linspace(0, 1, 120)
y = np.linspace(0, 2 * np.pi, 100).reshape(-1, 1)

frames = []
for i in range(10):
    x       += 1
    curVals  = f(x, y)
    frames.append(curVals)

cv0 = frames[0]
cf = ax.contourf(cv0, 200)
cb = fig.colorbar(cf, cax=cax)
tx = ax.set_title('Frame 0')

def animate(i):
    arr = frames[i]
    vmax     = np.max(arr)
    vmin     = np.min(arr)
    levels   = np.linspace(vmin, vmax, 200, endpoint = True)
    cf = ax.contourf(arr, vmax=vmax, vmin=vmin, levels=levels)
    cax.cla()
    fig.colorbar(cf, cax=cax)
    tx.set_text('Frame {0}'.format(i))

ani = animation.FuncAnimation(fig, animate, frames=10)

plt.show()

主要区别在于我在一个函数中进行关卡计算和轮廓修改,而不是创建一个艺术家列表。颜色栏有效,因为您可以清除前一帧中的轴并每帧重做一次。

使用contourcontourf时,必须执行此重做,因为您无法动态更改数据。但是,由于您绘制了如此多的轮廓级别并且结果看起来很平滑,我认为您可能最好使用imshow - 这意味着您实际上可以使用相同的艺术家并更改数据,并且颜色栏更新本身自动。它也快得多!

更好的版本

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from mpl_toolkits.axes_grid1 import make_axes_locatable

fig = plt.figure()
ax = fig.add_subplot(111)

# I like to position my colorbars this way, but you don't have to
div = make_axes_locatable(ax)
cax = div.append_axes('right', '5%', '5%')

def f(x, y):
    return np.exp(x) + np.sin(y)

x = np.linspace(0, 1, 120)
y = np.linspace(0, 2 * np.pi, 100).reshape(-1, 1)

# This is now a list of arrays rather than a list of artists
frames = []
for i in range(10):
    x       += 1
    curVals  = f(x, y)
    frames.append(curVals)

cv0 = frames[0]
im = ax.imshow(cv0, origin='lower') # Here make an AxesImage rather than contour
cb = fig.colorbar(im, cax=cax)
tx = ax.set_title('Frame 0')

def animate(i):
    arr = frames[i]
    vmax     = np.max(arr)
    vmin     = np.min(arr)
    im.set_data(arr)
    im.set_clim(vmin, vmax)
    tx.set_text('Frame {0}'.format(i))
    # In this version you don't have to do anything to the colorbar,
    # it updates itself when the mappable it watches (im) changes

ani = animation.FuncAnimation(fig, animate, frames=10)

plt.show()