当用户滚动到50px以上时，为类添加类？(Add class to an element when user scrolls to 50px above it?)

 通过添加颜色条后，可以将ax （带有标签的空轴）的位置更改为ax2的位置（显示数据的轴） 
 
ax.set_position(ax2.get_position())
 
 或者，通过从两个轴“钢化”空间来创建颜色条， 
 
cb = fig.colorbar(sm,ax=[ax,ax2], extend="both", label="units")
 
 这两个解决方案都可以在这个链接问题的答案中找到。 
 
 
 以下是问题实际范围之外的一些额外改进： 
 
ax.axis('scaled')
ax2.axis('scaled') 
 
 此外，如果ax2放在ax的顶部，这样contourf图不会与轴的脊椎重叠。 
 
# put `ax` on top, to let the contours not overlap the shown axes
ax.set_zorder(2)     
ax.patch.set_visible(False)
# ax2 will hold the plot, but has invisible labels
ax2 = fig.add_subplot(111,zorder=1)
 
 完整的代码： 
 
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import mlab, cm

delta = 0.5
extent = (-3, 4, -4, 3)
x = np.arange(-3.0, 4.001, delta)
y = np.arange(-4.0, 3.001, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z = (Z1 - Z2) * 10

levels = np.arange(-2.0, 1.601, 0.4) 

norm = cm.colors.Normalize(vmax=abs(Z).max(), vmin=-abs(Z).max())
cmap = cm.PRGn

# ax is empty
fig, ax = plt.subplots()
ax.set_navigate(False)
 # put `ax` on top, to let the contours not overlap the shown axes
ax.set_zorder(2)     
ax.patch.set_visible(False)
# ax2 will hold the plot, but has invisible labels
ax2 = fig.add_subplot(111,zorder=1)

ax2.contourf(X, Y, Z, levels,
                 cmap=cm.get_cmap(cmap, len(levels) - 1),
                 norm=norm,
                 )
ax2.axis("off")

ax.set_xlim(ax2.get_xlim())
ax.set_ylim(ax2.get_ylim())

#
# Declare and register callbacks
def on_lims_change(axes):
    # change limits of ax, when ax2 limits are changed.
    a=ax2.get_xlim()
    ax.set_xlim(0, a[1]-a[0])
    a=ax2.get_ylim()
    ax.set_ylim(0, a[1]-a[0])


sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm )
sm._A = []
cb = fig.colorbar(sm,ax=[ax,ax2], extend="both", label="units")
cb.ax.tick_params(labelsize=10)

ax2.callbacks.connect('xlim_changed', on_lims_change)
ax2.callbacks.connect('ylim_changed', on_lims_change)
ax.axis('scaled')
ax2.axis('scaled')
#ax.set_position(ax2.get_position())
# Show
plt.show()
 
  

You can change the position of ax (the empty axes with the labels) to the position of ax2 (the axes showing the data) after adding the colorbar via
 
ax.set_position(ax2.get_position())
 
Alternatively, create the colorbar by "steeling" the space from both axes,
 
cb = fig.colorbar(sm,ax=[ax,ax2], extend="both", label="units")
 
Both solutions are found in the answers to this linked question. 
 
 
 The following are some additional improvements outside the actual scope of the question: 
 
ax.axis('scaled')
ax2.axis('scaled') 
 
Additionally, put the ax on top if the ax2, such that the contourf plot does not overlap the axes spines.
 
# put `ax` on top, to let the contours not overlap the shown axes
ax.set_zorder(2)     
ax.patch.set_visible(False)
# ax2 will hold the plot, but has invisible labels
ax2 = fig.add_subplot(111,zorder=1)
 
Complete code:
 
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import mlab, cm

delta = 0.5
extent = (-3, 4, -4, 3)
x = np.arange(-3.0, 4.001, delta)
y = np.arange(-4.0, 3.001, delta)
X, Y = np.meshgrid(x, y)
Z1 = mlab.bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
Z2 = mlab.bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
Z = (Z1 - Z2) * 10

levels = np.arange(-2.0, 1.601, 0.4) 

norm = cm.colors.Normalize(vmax=abs(Z).max(), vmin=-abs(Z).max())
cmap = cm.PRGn

# ax is empty
fig, ax = plt.subplots()
ax.set_navigate(False)
 # put `ax` on top, to let the contours not overlap the shown axes
ax.set_zorder(2)     
ax.patch.set_visible(False)
# ax2 will hold the plot, but has invisible labels
ax2 = fig.add_subplot(111,zorder=1)

ax2.contourf(X, Y, Z, levels,
                 cmap=cm.get_cmap(cmap, len(levels) - 1),
                 norm=norm,
                 )
ax2.axis("off")

ax.set_xlim(ax2.get_xlim())
ax.set_ylim(ax2.get_ylim())

#
# Declare and register callbacks
def on_lims_change(axes):
    # change limits of ax, when ax2 limits are changed.
    a=ax2.get_xlim()
    ax.set_xlim(0, a[1]-a[0])
    a=ax2.get_ylim()
    ax.set_ylim(0, a[1]-a[0])


sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm )
sm._A = []
cb = fig.colorbar(sm,ax=[ax,ax2], extend="both", label="units")
cb.ax.tick_params(labelsize=10)

ax2.callbacks.connect('xlim_changed', on_lims_change)
ax2.callbacks.connect('ylim_changed', on_lims_change)
ax.axis('scaled')
ax2.axis('scaled')
#ax.set_position(ax2.get_position())
# Show
plt.show()