维护maptlotlib FuncAnimation的一个颜色条 [英] Maintaining one colorbar for maptlotlib FuncAnimation

问题描述

我制作了一个脚本，该脚本使用matplotlib的FuncAnimation函数为抛物面表面函数设置了一系列等高线图.我想添加一个颜色条，其颜色范围在整个动画中不会改变.我真的不知道该怎么做.脚本如下所示:

I've made a script which uses matplotlib's FuncAnimation function to animate a series of contour plots for paraboloid surface functions. I'd like to add a colorbar for which the range does not change throughout the entire animation. I really have no idea how to do this. The script is shown below:

import numpy as np
import itertools
import matplotlib.pyplot as plt
import matplotlib.mlab as ml
import matplotlib.animation as animation

#Generate some lists

def f(x,y,a):
    return a*(x**2+y**2)

avals = list(np.linspace(0,1,10))
xaxis = list(np.linspace(-2,2,9))
yaxis = list(np.linspace(-2,2,9))

xy = list(itertools.product(xaxis,yaxis))
xy = list(map(list,xy))
xy = np.array(xy)

x = xy[:,0]
y = xy[:,1]
x = list(x)
y = list(y)

zlist = []

for a in avals:
    z = []
    for i, xval in enumerate(x):
        z.append(f(x[i],y[i],a))
    zlist.append(z)

xi = np.linspace(min(x),max(x),len(x))
yi = np.linspace(min(y), max(y), len(y))

fig,ax = plt.subplots()

def animate(index):
    zi = ml.griddata(x, y, zlist[index], xi, yi, interp='linear')
    ax.clear()
    contourplot = ax.contourf(xi, yi, zi, cmap=plt.cm.hsv,origin='lower')
    #cbar = plt.colorbar(contourplot)
    ax.set_title('%03d'%(index))
    return ax

ani = animation.FuncAnimation(fig,animate,np.array([0,1,2,3,4,5,6,7,8,9]),interval=200,blit=False)
plt.show()

第42行是我尝试包含所述颜色条的尝试.这里的问题是，因为FuncAnimation多次调用绘制函数(每帧一次)，所以彩条被绘制多次，从而使动画混乱.我也想不出任何方法将颜色条实例化移动到动画功能之外，因为ax对象似乎是本地的.

Line 42 was my attempt at including said colorbar. The issue here is that because FuncAnimation calls the plotting function multiple times (once for each frame), the colorbar gets plotted multiple times thus messing up the animation. I also can't think of any way to move the colorbar instantiation outside of the animate function since the ax object appears to be local to it.

如何为整个动画放置一个颜色条?

How can I put one colorbar for the whole animation?

请注意，上面的代码是完全有效的代码.它应该可以在适当的python解释器上工作.

Please note the above is fully working code. It should work on the appropriate python interpreter.

推荐答案

我想这个想法是在更新函数之外创建一次轮廓图，并为其提供颜色条.然后，轮廓图将需要具有定义的级别，并且需要定义颜色范围.

I guess the idea would be to create a contour plot outside the updating function once and give it a colorbar. The contour plot would then need to have defined levels and the colorrange needs to be defined.

ax.contourf(..., levels=levels, vmin=zmin, vmax=zmax)

其中zmin和zmax是要显示的最小和最大数据，而levels是要使用的级别的列表或数组.

where zmin and zmax are the minimum and maximum data to be shown, and levels is the list or array of levels to use.

然后，在动画功能内部，您将只创建一个具有相同参数的新轮廓图，而完全不触摸颜色栏.

Then, inside the animating function, you would only create a new contour plot with those same parameters without touching the colorbar at all.

import numpy as np
import itertools
import matplotlib.pyplot as plt
import matplotlib.mlab as ml
import matplotlib.animation as animation

def f(x,y,a):
    return a*(x**2+y**2)

avals = list(np.linspace(0,1,10))
xaxis = list(np.linspace(-2,2,9))
yaxis = list(np.linspace(-2,2,9))

xy = list(itertools.product(xaxis,yaxis))
xy = np.array(list(map(list,xy)))

x = xy[:,0]
y = xy[:,1]

zlist = []

for a in avals:
    z = []
    for i, xval in enumerate(x):
        z.append(f(x[i],y[i],a))
    zlist.append(z)

xi = np.linspace(min(x),max(x),len(x))
yi = np.linspace(min(y), max(y), len(y))

zmin = min([min(zl) for zl in zlist])
zmax = max([max(zl) for zl in zlist])
levels = np.linspace(zmin, zmax,41)
kw = dict(levels=levels, cmap=plt.cm.hsv, vmin=zmin, vmax=zmax, origin='lower')

fig,ax = plt.subplots()
zi = ml.griddata(x, y, zlist[0], xi, yi, interp='linear')
contourplot = ax.contourf(xi, yi, zi, **kw)
cbar = plt.colorbar(contourplot)

def animate(index):
    zi = ml.griddata(x, y, zlist[index], xi, yi, interp='linear')
    ax.clear()
    ax.contourf(xi, yi, zi, **kw)
    ax.set_title('%03d'%(index))


ani = animation.FuncAnimation(fig,animate,10,interval=200,blit=False)
plt.show()

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