Python3.x 如何在 histplot 中标记核密度估计

我正在使用seaborn绘制直方图，以及KDE曲线和高斯拟合，但sns.histplot中的指令label = "KDE fit"显示为不适当的 colored颜色 ，因为它似乎引用了整个直方图……有没有办法特别标记KDE曲线，以便在legend框中显示为绿色实线(就像高斯拟合显示为红色虚线一样)？

我使用的完整代码如下:

import numpy as np
import matplotlib.pylab as plt
import seaborn as sns
import scipy.stats as stats
from scipy.stats import norm

# Generating data

np.random.seed(63123) 
data = np.random.normal(loc = 600, scale = 30, size = 20)

# Parameters for histogram plotting

min_val = data.min()
max_val = data.max()
val_width = max_val - min_val
n_bins = 7
bin_width = val_width/n_bins

list_xticks_raw = np.arange(min_val - bin_width/2, max_val + bin_width/2, bin_width).tolist()
list_xticks_round = [round(x) for x in list_xticks_raw]

# Histogram and Gaussian fit plotting

fig = plt.figure(figsize = (4,4))

h = sns.histplot(data = None, x = data , bins = n_bins, binrange=(min_val, max_val), discrete = False, shrink = 1.0,
             stat = "density", element = "bars", color = "green", kde = True, label = "KDE fit")

plt.xlim(min_val - bin_width/2, max_val + bin_width/2) # Define x-axis limits
plt.xticks(list_xticks_round)

mu, sigma = stats.norm.fit(data)
sorted_data = np.sort(data)
gaussian_fit = stats.norm.pdf(sorted_data, mu, sigma)
plt.plot(sorted_data, gaussian_fit, linestyle = "--", color = "red", label = "Gaussian fit")

plt.legend()

plt.show()