kde plot

kdeplot 知乎； kdeplot和distplot; 绘制核密度曲线图

seaborn学习笔记（五）：绘制多子图 ; Python中取余、除法、取整的操作逻辑; Seaborn:如何在分布图中添加垂直线 (sns.distplot)

plt.legned(loc); legend 的位置

matplotlib colormap_reference

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结果的分析：核密度图解释

columns = [r'\alpha', r'\beta', 'm', r'\theta_1', r'\theta_2', r'\omega_1', r'\omega_2', r'LLF']
fig, axes = plt.subplots(4, 2, figsize=(10, 10))
plt.suptitle('KDE Plot of Garch-Midas Parameters', fontsize=12, weight='bold')
plt.subplots_adjust(left=0.125, right=0.9, top=0.935, bottom=0.110)
plt.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0.25, hspace=0.3)
for index, column in enumerate(columns):
    i = index // 2
    j = index % 2
    # print(index, i, j)
    sns.kdeplot(gm_p.values[:, index],  linewidth=1, linestyle='solid',
                fill=True, color='#DC143C', label=f'column1 ${column}$', ax=axes[i][j])
    sns.kdeplot(gm_p.values[:sz_china, index],  linewidth=1, linestyle='solid', legend=True,
                fill=True, color='teal', label=f'column2  ${column}$', ax=axes[i][j])
    sns.kdeplot(gm_p.values[sz_china:, index],  linewidth=1, linestyle='solid',
                fill=True,  color='#6495ED', label=f'column3  ${column}$', ax=axes[i][j])

    sns.rugplot(gm_p.values[:, index], color='#DC143C', alpha=0.5, ax=axes[i][j])
    sns.rugplot(gm_p.values[:sz_china, index], color='teal', alpha=0.5, ax=axes[i][j])
    sns.rugplot(gm_p.values[sz_china:, index], color='#6495ED', alpha=0.5, ax=axes[i][j])

    # mean vline
    axes[i][j].axvline(np.mean(gm_p.values[:, index]), linewidth=1, color='#DC143C')
    axes[i][j].axvline(np.mean(gm_p.values[:sz_china, index]), linewidth=1, color='teal')
    axes[i][j].axvline(np.mean(gm_p.values[sz_china:, index]), linewidth=1, color='#6495ED')

    # legend
    axes[i][j].legend(loc=0, frameon=False, prop={'style': 'italic', 'weight': 'bold'})
    axes[i][j].autoscale(enable=True, axis='x', tight=False)

    # x-axis, y-axis, font
    for size in axes[i][j].get_xticklabels():  # 获取x轴上所有坐标，并设置字号
        size.set_fontname('Times New Roman')
    for size in axes[i][j].get_yticklabels():  # 获取x轴上所有坐标，并设置字号
        size.set_fontname('Times New Roman')

    # ticker
    axes[i][j].tick_params(axis='both', which='major', labelsize=9, bottom=True, left=True)
plt.tight_layout()
plt.savefig('./figures/kde of garch-midas parameters.pdf')
plt.close()