如何在动画期间更新子图的颜色条？

问题描述

下面是我的带有子情节的示范动画。我有两个颜色条：本地和全局。我找到了一种在动画期间更新全局颜色条的方法。但是，我找不到更新本地的方法。

在当前的实现中，在每次迭代中，我都会得到一个额外的颜色条（参见 attached）。鉴于代码结构，有没有办法清除/更新它？

import numpy as np
from scipy import interpolate
from scipy.interpolate import griddata
import matplotlib.pyplot as plt
import math
from scipy.interpolate import RectBivariateSpline
import matplotlib.animation as animation

# Animation with subplots

fig,axes = plt.subplots(nrows=2,ncols=2,figsize=(15,15),subplot_kw=dict(projection='polar'))

def myValues(*args):
    azimuths = np.radians(np.linspace(0,360,20))
    zeniths  = np.arange(0,150,10)

    rho,theta = np.meshgrid(zeniths,azimuths)
    values     = np.random.random((azimuths.size,zeniths.size))
    
    return theta,rho,values

# ---------------------------------Sub-plot #1 ---------------------------------
theta,values = myValues()
im1 = axes.flat[0].contourf(theta,values,cmap='jet')
fig.colorbar(im1,ax=axes.flat[0]) # local colorbar

# ---------------------------------Sub-plot #2 ---------------------------------
theta,values = myValues()
im2 = axes.flat[1].contourf(theta,cmap='jet')

# ---------------------------------Sub-plot #3 ---------------------------------
theta,values = myValues()
im3 = axes.flat[2].contourf(theta,cmap='jet')

# ---------------------------------Sub-plot #4 ---------------------------------
theta,values = myValues()
im4 = axes.flat[3].contourf(theta,cmap='jet')

# Global colorbar
fig.subplots_adjust(right=0.94)
cax = fig.add_axes([0.95,0.15,0.02,0.7])
gcb = fig.colorbar(im4,cax=cax)

# This function is called periodically from FuncAnimation
def updatefig(*args):
    
    global im1,im2,im3,im4,lcb,gcb
    
    # ---------------------------------Sub-plot #1 ---------------------------------
    theta,values = myValues()
    
    for c in im1.collections:
        c.remove()  # removes only the contours,leaves the rest intact
    
    im1 = axes.flat[0].contourf(theta,cmap='jet')
    
    # How to update this local colorbar?
    lcb = fig.colorbar(im1,ax=axes.flat[0])

    # ---------------------------------Sub-plot #2 ---------------------------------
    theta,values = myValues()
    
    for c in im2.collections:
        c.remove()
    
    im2 = axes.flat[1].contourf(theta,cmap='jet')

    # ---------------------------------Sub-plot #3 ---------------------------------
    theta,values = myValues()
    
    for c in im3.collections:
        c.remove()
    
    im3 = axes.flat[2].contourf(theta,cmap='jet')

    # ---------------------------------Sub-plot #4 ---------------------------------
    theta,values = myValues()
    
    for c in im4.collections:
        c.remove()
    
    im4 = axes.flat[3].contourf(theta,cmap='jet')
    
    # Update global colorbar
    cax.cla()
    gcb = fig.colorbar(im4,cax=cax)
    
# Set up plot to call animate() function periodically
ani = animation.FuncAnimation(fig,updatefig)
plt.show()

这篇文章 https://stackoverflow.com/questions/39472017/how-to-animate-the-colorbar-in-matplotlib 似乎是相关的，但我无法采用建议的带有子图的我的案例的解决方案。

解决方法

这是我的解决方法：

# Animation with subplots
from mpl_toolkits.axes_grid1 import make_axes_locatable

fig,axes = plt.subplots(nrows=2,ncols=2,figsize=(15,15),subplot_kw=dict(projection='polar'))

def myValues(*args):
    azimuths = np.radians(np.linspace(0,360,20))
    zeniths  = np.arange(0,150,10)

    rho,theta = np.meshgrid(zeniths,azimuths)
    values     = np.random.random((azimuths.size,zeniths.size))
    
    return theta,rho,values

# ---------------------------------Sub-plot #1 ---------------------------------
theta,values = myValues()
im1 = axes.flat[0].contourf(theta,values,cmap='jet')

#Local colorbar
fig.subplots_adjust(right=0.47)
lcb_cax = fig.add_axes([0.5,0.53,0.02,0.35])
lcb = fig.colorbar(im1,cax=lcb_cax)

# ---------------------------------Sub-plot #2 ---------------------------------
theta,values = myValues()
im2 = axes.flat[1].contourf(theta,cmap='jet')

# ---------------------------------Sub-plot #3 ---------------------------------
theta,values = myValues()
im3 = axes.flat[2].contourf(theta,cmap='jet')

# ---------------------------------Sub-plot #4 ---------------------------------
theta,values = myValues()
im4 = axes.flat[3].contourf(theta,cmap='jet')

# Global colorbar
fig.subplots_adjust(right=0.94)
cax = fig.add_axes([0.95,0.15,0.7])
gcb = fig.colorbar(im4,cax=cax)

# This function is called periodically from FuncAnimation
def updatefig(*args):
    
    global im1,im2,im3,im4,lcb,gcb
    
    # ---------------------------------Sub-plot #1 ---------------------------------
    theta,values = myValues()
    
    for c in im1.collections:
        c.remove()  # removes only the contours,leaves the rest intact
    
    im1 = axes.flat[0].contourf(theta,cmap='jet')
    
    # How to update this local colorbar?
    lcb_cax.cla()
    lcb = fig.colorbar(im1,cax=lcb_cax)

    # ---------------------------------Sub-plot #2 ---------------------------------
    theta,values = myValues()
    
    for c in im2.collections:
        c.remove()
    
    im2 = axes.flat[1].contourf(theta,cmap='jet')

    # ---------------------------------Sub-plot #3 ---------------------------------
    theta,values = myValues()
    
    for c in im3.collections:
        c.remove()
    
    im3 = axes.flat[2].contourf(theta,cmap='jet')

    # ---------------------------------Sub-plot #4 ---------------------------------
    theta,values = myValues()
    
    for c in im4.collections:
        c.remove()
    
    im4 = axes.flat[3].contourf(theta,cmap='jet')
    
    # Update global colorbar
    gcb_cax.cla()
    gcb = fig.colorbar(im4,cax=gcb_cax)
    
# Set up plot to call animate() function periodically
ani = animation.FuncAnimation(fig,updatefig)

plt.show()

很可能有更好的方法来做到这一点。如果你知道，请告诉我！