如何在seaborn distplot的模式下畫一條垂直線

Question

我剛剛學會了如何使用seaborn Python 模塊繪制密度圖：

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')

如何在此distplot上以該密度曲線的模式繪制一條垂直線？

謝謝，

Answer 1

我找到了解決方案：

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')

Answer 2

您可以提取生成曲線的 x 和 y 值，並找到最高 y 值的眾數。

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()