如何摆脱这个虚拟的可映射对象，仍然在Matplotlib中绘制颜色栏？

我有下面的代码来绘制圆并将它们添加到ax中

我根据颜色条给圆上色

但是，要将颜色条添加到绘图中，我使用sc=plot.scatter。。。并使用这个虚拟sc放置颜色条。因为plt.colorbarsc，。。。需要可映射的参数。我怎样才能摆脱这个虚拟sc，仍然画我的色条

import matplotlib
import numpy as np
import os
import matplotlib as mpl
from matplotlib.colors import Normalize
import matplotlib.cm as matplotlib_cm
from matplotlib import pyplot as plt

print(matplotlib.__version__)

row_list=['row1', 'row2', 'row3']
column_list=[2]
maxProcessiveGroupLength=2
index = column_list.index(maxProcessiveGroupLength)

plot1,panel1 = plt.subplots(figsize=(20+1.5*len(column_list), 10+1.5*len(row_list)))
plt.rc('axes', edgecolor='lightgray')

#make aspect ratio square
panel1.set_aspect(1.0)
panel1.text(0.1, 1.2, 'DEBUG', horizontalalignment='center', verticalalignment='top', fontsize=60, fontweight='bold', fontname='Arial',transform=panel1.transAxes)

if (len(column_list) > 1):
    panel1.set_xlim([1, index + 1])
    panel1.set_xticks(np.arange(0, index + 2, 1))
else:
    panel1.set_xlim([0, len(column_list)])
    panel1.set_xticks(np.arange(0, len(column_list)+1, 1))

if (len(row_list) > 1):
    panel1.set_ylim([1, len(row_list)])
else:
    panel1.set_ylim([0, len(row_list)])

panel1.set_yticks(np.arange(0, len(row_list) + 1, 1))

panel1.set_facecolor('white')
panel1.grid(color='black')

for edge, spine in panel1.spines.items():
    spine.set_visible(True)
    spine.set_color('black')

xlabels = None
if (index is not None):
    xlabels = column_list[0:index + 1]
ylabels = row_list

cmap = matplotlib_cm.get_cmap('Blues')  # Looks better
v_min = 2
v_max = 20
norm = Normalize(v_min, v_max)
bounds = np.arange(v_min, v_max+1, 2)

# Plot the circles with color
for row_index, row in enumerate(row_list):
    for column_index, processive_group_length in enumerate(column_list):
        radius=0.35
        color=10+column_index*3+row_index*3
        circle = plt.Circle((column_index + 0.5, row_index + 0.5), radius,color=cmap(norm(color)), fill=True)
        panel1.add_patch(circle)

# Used for scatter plot
x = []
y = []
c = []

for row_index, processiveGroupLength in enumerate(row_list):
    x.append(row_index)
    y.append(row_index)
    c.append(0.5)

# This code defines the ticks on the color bar
# plot the scatter plot
sc = plt.scatter(x, y, s=0, c=c, cmap=cmap, vmin=v_min, vmax=v_max, edgecolors='black')

# colorbar to the bottom
cb = plt.colorbar(sc ,orientation='horizontal')  # this works because of the scatter
cb.ax.set_xlabel("colorbar label", fontsize=50, labelpad=25)

# common for horizontal colorbar and vertical colorbar
cbax = cb.ax
cbax.tick_params(labelsize=40)
text_x = cbax.xaxis.label
text_y = cbax.yaxis.label
font = mpl.font_manager.FontProperties(size=40)
text_x.set_font_properties(font)
text_y.set_font_properties(font)

# CODE GOES HERE TO CENTER X-AXIS LABELS...
panel1.set_xticklabels([])
mticks = panel1.get_xticks()
panel1.set_xticks((mticks[:-1] + mticks[1:]) / 2, minor=True)
panel1.tick_params(axis='x', which='minor', length=0, labelsize=50)

if xlabels is not None:
    panel1.set_xticklabels(xlabels,minor=True)

panel1.xaxis.set_ticks_position('top')

plt.tick_params(
    axis='x',  # changes apply to the x-axis
    which='major',  # both major and minor ticks are affected
    bottom=False,  # ticks along the bottom edge are off
    top=False)  # labels along the bottom edge are off

# CODE GOES HERE TO CENTER Y-AXIS LABELS...
panel1.set_yticklabels([])
mticks = panel1.get_yticks()
panel1.set_yticks((mticks[:-1] + mticks[1:]) / 2, minor=True)
panel1.tick_params(axis='y', which='minor', length=0, labelsize=50)
panel1.set_yticklabels(ylabels, minor=True)  # fontsize

plt.tick_params(
    axis='y',  # changes apply to the x-axis
    which='major',  # both major and minor ticks are affected
    left=False)  # labels along the bottom edge are off

plt.show()

根据以下文件：

注意，可以动态创建ScalarMapable来生成 未附加到以前绘制的艺术家的色条

在您的示例中，以下允许在不使用散点图的情况下创建相同的颜色栏：

cb = plt.colorbar(mpl.cm.ScalarMappable(norm=norm, cmap=cmap), orientation='horizontal')

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谢谢@jf_u，我做了一些试验，但这次没有。非常感谢。