如何在 seaborn distplot 的模式下画一条垂直线

Question

我刚刚学会了如何使用seaborn Python 模块绘制密度图：

import numpy as np
import torch
from matplotlib import pyplot as plt
from matplotlib.pyplot import (plot, savefig, xlim, figure,
                              ylim, legend, boxplot, setp,
                              axes, xlabel, ylabel, xticks,
                              axvline)
import seaborn as sns

layer1_G1_G2 = [-0.05567627772688866,
 -0.06829605251550674,
 -0.0721447765827179,
 -0.05942181497812271,
 -0.061410266906023026,
 -0.062010858207941055,
 -0.05238522216677666,
 -0.057129692286252975,
 -0.06323938071727753,
 -0.07018601894378662,
 -0.05972284823656082,
 -0.06124034896492958,
 -0.06971242278814316,
 -0.06730005890130997]

def make_density(layer_list,color, layer_num):

    layer_list_tensor = torch.tensor(layer_list)
    
    # Plot formatting
    plt.title('Density Plot of Median Stn. MC-Losses at Layer ' + layer_num)
    plt.xlabel('MC-Loss')
    plt.ylabel('Density')
    plt.xlim(-0.2,0.05)
    plt.ylim(0, 85)
    min_ylim, max_ylim = plt.ylim()
    
    # Draw the density plot
    sns.distplot(layer_list, hist = False, kde = True,
                 kde_kws = {'linewidth': 2}, color=color)

# plot the density plot
# the resulting density plot is shown below
>>> make_density(layer1_G1_G2, 'green','1')

如何在这个distplot上以密度曲线的模式画一条垂直线？

谢谢，

Answer 1

您可以提取生成曲线的 x 和 y 值，并找到最高 y 值的众数。

from matplotlib import pyplot as plt
import seaborn as sns

layer1_G1_G2 = [-0.05567627772688866, -0.06829605251550674, -0.0721447765827179, -0.05942181497812271, -0.061410266906023026, -0.062010858207941055, -0.05238522216677666, -0.057129692286252975, -0.06323938071727753, -0.07018601894378662, -0.05972284823656082, -0.06124034896492958, -0.06971242278814316, -0.06730005890130997]

def make_density(layer_list, color, layer_num):
    # Draw the density plot
    ax = sns.distplot(layer_list, hist=False, kde=True, kde_kws={'linewidth': 2}, color=color)
    x = ax.lines[0].get_xdata()
    y = ax.lines[0].get_ydata()
    mode_idx = y.argmax()
    ax.vlines(x[mode_idx], 0, y[mode_idx], color='crimson', ls=':')

    # Plot formatting
    ax.set_title('Density Plot of Median Stn. MC-Losses at Layer ' + layer_num)
    ax.set_xlabel('MC-Loss')
    ax.set_ylabel('Density')
    ax.autoscale(axis='x', tight=True)
    ax.set_ylim(ymin=0)

make_density(layer1_G1_G2, 'green', '1')
plt.show()

Answer 2

我找到了解决办法：

def make_density(layer_list,color, layer_num):

    
    # Plot formatting
    plt.title('Density Plot of Median Stn. MC-Losses at Layer ' + layer_num)
    plt.xlabel('MC-Loss')
    plt.ylabel('Density')
    plt.xlim(-0.2,0.05)
    plt.ylim(0, 85)
    min_ylim, max_ylim = plt.ylim()
    
    
    
    # Draw the density plot
    sns.distplot(layer_list, hist = False, kde = True,
                 kde_kws = {'linewidth': 2}, color=color)
    
    dens_list = sns.distplot(layer1_G1_G2, hist = False, kde = True,
             kde_kws = {'linewidth': 2}, color='green').get_lines()[0].get_data()[1].tolist()
                    
    max_dens_index = dens_list.index(max(dens_list))
    
    mode = sns.distplot(layer1_G1_G2, hist = False, kde = True,
             kde_kws = {'linewidth': 2}, color='green').get_lines()[0].get_data()[0].tolist()[max_dens_index]
  
    plt.axvline(mode, color='orange', linestyle='dashed', linewidth=1.5)

    plt.text(mode * 0.87, 80, 'mode: {:.2f}'.format(mode))

>>> make_density(layer1_G1_G2, 'green','1')