如何解决颜色条最小/最大颜色与绘制的最小/最大值不匹配

我正在绘制一个 NetworkX 图并使用加权值对边进行着色。我正在向绘图中添加一个颜色条，并希望将颜色条的最小/最大值保持在预先确定的值上。

我的计划是迭代多次模拟并为每次迭代获得一个图表。通过这样做，我应该能够看到加权边缘颜色随时间的演变，始终与颜色栏中定义的相同（预定）最小/最大限制进行比较。

我做错了，因为在每次迭代图形中看到的边权重的最小/最大值总是与颜色条的最小/最大颜色匹配，不管边值在每次迭代中的值与颜色条最小/最大限制。

似乎在某些时候，Graph 边的 Min/Max 值和 Colorbar 的预定 Min/Max 值被置于相同的颜色级别，而 Colorbar Min/Max 值（和相关颜色）应该规则在 Graph 颜色绘制上。

提前致谢。

找到我正在运行的代码的下一部分：

图形绘制：

 nx.draw(\
                            G,pos,# label font size
                            font_size = 8,# label font weight
                            font_weight = 'bold',# label font color
                            font_color = 'r',# label font familly
                            font_family = 'sans-serif',# node label print or not 
                            with_labels = True,# node labels
                            labels = df_nodes_names['Bus Name'].to_dict(),\
                        # horizontalalignment ({‘center’,‘right’,‘left’}) – Horizontal alignment (default=’center’)
                            horizontalalignment = 'right',# verticalalignment ({‘center’,‘top’,‘bottom’,‘baseline’,‘center_baseline’}) 
                            verticalalignment = 'baseline',# node contour line width
                            linewidths = [2.0 if entry == 3 else 0.5 for entry in df_nodes_types.BusType],# node edge size,Confusing!!! Node contour line color,different from 'edge_color'
                            edgecolors = 'lightgrey',# node shape
                            node_shape = 'o',# node size,node_size can be scalar or array 
                            node_size = [200 if entry == 3 else 50 for entry in df_nodes_types.BusType],# node fill color
                            node_color = 'whitesmoke',# # node min attribute value for lowest color in colormap palet
                            # vmin = df_branches_toPlot[selection_name][1],\
                        # # node max attribute value for highest color in colormap palet
                            # vmax = df_branches_toPlot[selection_name][2],\
                        # # node colormap deFinition
                            cmap = plt.set_cmap('jet'),\
                        # arrowstyle in directed graphs
                            arrowstyle="->",# arrowsize in directed graphs
                            arrowsize=10,# edge fill color
                            edge_color = df_branches_aux[selection_name],# edge width
                            width = 4.0,# edge colormap deFinition
                            edge_cmap = plt.set_cmap('jet'))

颜色条设置：

颜色条

            # --------
            # set Scalar Mappable for the colormar
            vmin = df_branches_toPlot[selection_name][1]       # minimun value for lowest color in 'cmap',read from dataframe,position [1]=min
            vmax = df_branches_toPlot[selection_name][2]       # maximum value for highest color in 'cmap' read from dataframe,position [2]=max
            sm = plt.cm.ScalarMappable(
                    cmap = plt.set_cmap('jet'),\
                    norm = plt.normalize(vmin=vmin,vmax=vmax)
                    )
            sm.set_array([])
            
            cbar = plt.colorbar(
                # mappable
                    mappable = sm,# orientation
                    orientation = 'vertical',# location,'orientation' and 'location' are mutually related,for this reason only one is set. 
                    # location = 'right',# fraction,fraction of original axes to use for colorbar
                    fraction = 0.1,# shrink,Fraction by which to multiply the size of the colorbar.
                    shrink = 0.85)