使用带有辅助y轴的colorbar

Question

我正在尝试将颜色条添加到具有辅助y轴的图表中。我的困难的最小例子如下。麻烦的是我不能将颜色条添加到AxesSubplot对象，并直接添加它作为plt.colorbar将它放在我的图形之上 - 看它是如何与最右边的y轴重叠。我怎样才能解决这个问题？欢呼声。

import matplotlib.pyplot as plt
import numpy as np
import scipy.interpolate

time=[]
temp=[]
temp_f=[]
height=[]
for ti in np.arange( 0, 10, 0.5 ):
    for te in np.arange( -12, 12, 0.5 ):
        height.append( np.sqrt(1+ti)/(1+te*te)+ti*te/12.5 )
        time.append(ti)
        temp.append(te)
        temp_f.append( 32+9.0*te/5)

time=np.array(time)
temp=np.array(temp)
temp_f=np.array(temp_f)
height=np.array(height)

xi, yi = np.linspace(time.min(), time.max(),25), np.linspace(temp.min(), temp.max(), 25)
xi, yi = np.meshgrid(xi, yi)

rbf = scipy.interpolate.Rbf(time, temp, height, function='linear')
zi = rbf(xi, yi)

fig = plt.figure()
ax1 = plt.gca()
ax1.set_xlabel( "Time (s)" )
ax1.set_ylabel( "Celsius" )

ax2 = ax1.twinx()
ax2.set_ylabel( "Fahrenheit" )
ax2.set_ylim( [temp_f.min(), temp_f.max()] )

img = ax1.imshow( zi, vmin=height.min(), vmax=height.max(), origin='lower', 
       extent=[time.min(), time.max(), temp.min(), temp.max()],
       aspect='auto', cmap='YlOrRd')

plt.colorbar(img, label=r"Height (cm)",format='%1.1f', ax=ax1)

plt.show()

Answer 1

See positioning the colorbar.

You can manually specify the location of the colorbar by:

cbaxes = fig.add_axes([1, 0.15, 0.03, 0.7])
plt.colorbar(img, label=r"Height (cm)",format='%1.1f', ax=ax1, cax=cbaxes)

Answer 2

plt.colorbar does a good job for simple plots with one axes. With more complex setups it can get confused. So it is better to manually setup the axes for the colorbar. You can use the subplots function for that. By supplying gridspec_kw you can tell the underlying GridSpec object how you want the widths to be specified:

fig, [ax1, cax] = plt.subplots(1,2, gridspec_kw=dict(width_ratios=[10,1]))

when creating the colorbar you want to specify the axes which should be used to create the colorbar in:

plt.colorbar(img, label=r"Height (cm)",format='%1.1f', ax=ax1, cax=cax)

So with the full code:

import matplotlib.pyplot as plt
import numpy as np
import scipy.interpolate

time=[]
temp=[]
temp_f=[]
height=[]
for ti in np.arange( 0, 10, 0.5 ):
    for te in np.arange( -12, 12, 0.5 ):
        height.append( np.sqrt(1+ti)/(1+te*te)+ti*te/12.5 )
        time.append(ti)
        temp.append(te)
        temp_f.append( 32+9.0*te/5)

time=np.array(time)
temp=np.array(temp)
temp_f=np.array(temp_f)
height=np.array(height)

xi, yi = np.linspace(time.min(), time.max(),25), np.linspace(temp.min(), temp.max(), 25)
xi, yi = np.meshgrid(xi, yi)

rbf = scipy.interpolate.Rbf(time, temp, height, function='linear')
zi = rbf(xi, yi)

fig, [ax1, cax] = plt.subplots(1,2, gridspec_kw=dict(width_ratios=[10,1]))
ax1.set_xlabel( "Time (s)" )
ax1.set_ylabel( "Celsius" )

ax2 = ax1.twinx()
ax2.set_ylabel( "Fahrenheit" )
ax2.set_ylim( [temp_f.min(), temp_f.max()] )

img = ax1.imshow( zi, vmin=height.min(), vmax=height.max(), origin='lower', 
       extent=[time.min(), time.max(), temp.min(), temp.max()],
       aspect='auto', cmap='YlOrRd')

plt.colorbar(img, label=r"Height (cm)",format='%1.1f', ax=ax1, cax=cax)

plt.show()

You get: