如何在 animation 期间更新子图的颜色条？

Question

Below is my exemplary animation with sub-plots. I have two colorbars: local and global. I found a way to update the global colorbar during animation. However, I can't find a way to update the local one.

In the current implementation, in every iteration I get an extra colorbar (see attached ). Given the code structure, is there a way to clear/update it?

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, rho, values = myValues()
im1 = axes.flat[0].contourf(theta, rho, values, 150, cmap='jet')
fig.colorbar(im1, ax=axes.flat[0]) # local colorbar

# ---------------------------------Sub-plot #2 ---------------------------------
theta, rho, values = myValues()
im2 = axes.flat[1].contourf(theta, rho, values, 150, cmap='jet')

# ---------------------------------Sub-plot #3 ---------------------------------
theta, rho, values = myValues()
im3 = axes.flat[2].contourf(theta, rho, values, 150, cmap='jet')

# ---------------------------------Sub-plot #4 ---------------------------------
theta, rho, values = myValues()
im4 = axes.flat[3].contourf(theta, rho, values, 150, 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, rho, values = myValues()
    
    for c in im1.collections:
        c.remove()  # removes only the contours, leaves the rest intact
    
    im1 = axes.flat[0].contourf(theta, rho, values, 150, cmap='jet')
    
    # How to update this local colorbar?
    lcb = fig.colorbar(im1, ax=axes.flat[0])

    # ---------------------------------Sub-plot #2 ---------------------------------
    theta, rho, values = myValues()
    
    for c in im2.collections:
        c.remove()
    
    im2 = axes.flat[1].contourf(theta, rho, values, 150, cmap='jet')

    # ---------------------------------Sub-plot #3 ---------------------------------
    theta, rho, values = myValues()
    
    for c in im3.collections:
        c.remove()
    
    im3 = axes.flat[2].contourf(theta, rho, values, 150, cmap='jet')

    # ---------------------------------Sub-plot #4 ---------------------------------
    theta, rho, values = myValues()
    
    for c in im4.collections:
        c.remove()
    
    im4 = axes.flat[3].contourf(theta, rho, values, 150, 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()

This post seems to be relevant, but I was unable to adopt the suggested solution(s) to my case with subplots.

Answer 1

Here is my workaround:

# 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, rho, values = myValues()
im1 = axes.flat[0].contourf(theta, rho, values, 150, 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, rho, values = myValues()
im2 = axes.flat[1].contourf(theta, rho, values, 150, cmap='jet')

# ---------------------------------Sub-plot #3 ---------------------------------
theta, rho, values = myValues()
im3 = axes.flat[2].contourf(theta, rho, values, 150, cmap='jet')

# ---------------------------------Sub-plot #4 ---------------------------------
theta, rho, values = myValues()
im4 = axes.flat[3].contourf(theta, rho, values, 150, 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, rho, values = myValues()
    
    for c in im1.collections:
        c.remove()  # removes only the contours, leaves the rest intact
    
    im1 = axes.flat[0].contourf(theta, rho, values, 150, cmap='jet')
    
    # How to update this local colorbar?
    lcb_cax.cla()
    lcb = fig.colorbar(im1, cax=lcb_cax)

    # ---------------------------------Sub-plot #2 ---------------------------------
    theta, rho, values = myValues()
    
    for c in im2.collections:
        c.remove()
    
    im2 = axes.flat[1].contourf(theta, rho, values, 150, cmap='jet')

    # ---------------------------------Sub-plot #3 ---------------------------------
    theta, rho, values = myValues()
    
    for c in im3.collections:
        c.remove()
    
    im3 = axes.flat[2].contourf(theta, rho, values, 150, cmap='jet')

    # ---------------------------------Sub-plot #4 ---------------------------------
    theta, rho, values = myValues()
    
    for c in im4.collections:
        c.remove()
    
    im4 = axes.flat[3].contourf(theta, rho, values, 150, 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()

Most likely, there is a better way to do this. Let me know if you know one!