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python - 如何使用 matplotlib/seabornn 将边缘线添加到图例上的标记

问题描述

我有一个带有图例的气泡图，显示了按颜色和大小区分的两个类别，散点图上的标记有黑色边缘颜色，我喜欢图例中显示的标记也有它，有人知道我该怎么做吗？

我正在使用 seaborn 散点图来生成图表

Summary = pd.read_csv("Summary.csv")

####################################################################################
# Plot the scatterplot
####################################################################################

f, (ax1, ax2) = plt.subplots(ncols=2, nrows=1, sharey=True, figsize=(8.27,5.8))
#----------------------------------------------------------------------------------------
# add a big axes, hide frame, common axis labels
#----------------------------------------------------------------------------------------
f.add_subplot(111, frameon=False)
# hide tick and tick label of the big axes
plt.tick_params(labelcolor='none', top=False, bottom=False, left=False, right=False)
plt.grid(False)
plt.xlabel('T$_{s}$ - T$_{sat}$ [$^{\circ}$C]', fontsize=14)
plt.ylabel('Heat Flux [W$\cdot$cm$^{-2}$]', fontsize=14)
#----------------------------------------------------------------------------------------

# Change the minimum and maximum point size
ax=sns.scatterplot(x='T_surf - T_sat [C]', y='Heat Flux [W/cm2]', data=Summary, # Choose the x and y values and the dataframe 
                     size='Mass flux [kg$\cdot$m$^{-2}$$\cdot$s$^{-1}$]', # Size of markers
                     hue='Enhanced Surface', # Color by surface type
                     #color='Greys',
                     alpha=1.0,
                     #style='Enhanced Surface', # Marker by surface type
                     sizes=(20, 700), # minimum and maximum marker size
                     palette = 'Blues',
                     #markers=["X","d", "*","s"], # Change the markers' style
                     markers='o',
                     edgecolor= "Black", # Change the edge color of the markers
                     linewidth=0.5, # Change the edge linewidth of the markers
                     legend=False,
                     ax=ax1
                    )

ax=sns.scatterplot(x='T_surf - T_sat [C]', y='Heat Flux [W/cm2]', data=Summary, # Choose the x and y values and the dataframe 
                     size='Mass flux [kg$\cdot$m$^{-2}$$\cdot$s$^{-1}$]', # Size of markers by population
                     hue='Enhanced Surface', # Color by surface type
                     #cmap='Greys',
                     alpha=1.0,
                     #style='Enhanced Surface', # Marker by surface type
                     sizes=(20, 700), # minimum and maximum marker size
                     palette = 'Blues',
                     #markers=["X","d", "*","s"], # Change the markers' style
                     markers='o',
                     edgecolor= "Black", # Change the edge color of the markers
                     linewidth=0.5, # Change the edge linewidth of the markers
                     legend='auto',
                     ax=ax2
                    )


ax1.set_xlim(-60, 120)
ax2.set_xlim(790, 810)

# labels = ax1.get_legend_handles_labels()
####################################################################################
# Use the matplotlib library to edit the plot
####################################################################################

#Legend
lgd = ax2.legend(loc="upper right", frameon = 0.5, framealpha=0.8, # Create a legend and define its location, frame and frame alpha
                  edgecolor='white', facecolor='white', ncol=2, # Edgecolor, facecolor and the number of columns
                  title='', fontsize=10, # the title and the font size
                  handlelength=1, handleheight=2, columnspacing = 1.0, labelspacing=1.5,
                  markerscale=1.0, markerfirst = False)

气泡图

标签： pythonmatplotlibseabornlegendscatter-plot

解决方案

您可以按照自己的方式创建情节seaborn，然后直接调整图例样式。

每个ha手柄都是一个matplotlib.collections.PathCollection，我已将边缘颜色设置为red此处，以便您可以看到差异。

import seaborn as sns

tips = sns.load_dataset("tips")

fig, ax = plt.subplots(figsize=(4,4))
sns.scatterplot(data=tips, x="total_bill", y="tip", style="day", ax=ax)

# Get the legend handles
handles, labels = ax.get_legend_handles_labels()

# Iterate through the handles and call `set_edgecolor` on each
for ha in handles:
    ha.set_edgecolor("red")

# Use `ax.legend` to set the modified handles and labels
lgd = ax.legend(
    handles, 
    labels,
    loc="upper left", 
    ncol=2,
)

产生：

具有修改的图例样式的散点图

或者，正如mwaskom建议的那样，修改艺术家以避免重绘图例：

tips = sns.load_dataset("tips")

fig, ax = plt.subplots(figsize=(4,4))
sns.scatterplot(data=tips, x="total_bill", y="tip", style="day", ax=ax)

# Place the legend
lgd = ax.legend(
    loc="upper left", 
    ncol=2,
)
# Modify the point edge colour
for ha in ax.legend_.legendHandles:
    ha.set_edgecolor("red")

产生相同的情节。

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