哔哔one
				在 R 中,您可以像这样非常接近:library(ggridges)set.seed(69)df <- data.frame(x = as.vector(sapply(14:10, function(i) rnorm(30, i, 2))),                 group = rep(letters[1:5], each = 30))ggplot(df, aes(x, y = group, fill = group)) +   geom_vline(aes(xintercept = 10), size = 2, color = "#5078be") +  geom_density_ridges(size = 2, aes(color = group)) +  geom_vline(aes(xintercept = 3), size = 2) +  scale_fill_manual(values = c("#8f4b4a", "#c08f33", "#e2baba", "#ffe2ae", "#83a8f1")) +  scale_colour_manual(values = c("#5c1a08", "#8c5b01", "#af8987", "#d2ab83", "#5078be")) +  theme_void() +  theme(legend.position = "none")
				
			
			
			
				
				呼啦一阵风
				您可以使用 z 轴来做到这一点。您仍然可以根据需要调整设计并隐藏轴等。from scipy import expimport matplotlib.pyplot as pltimport numpy as npfrom mpl_toolkits import mplot3ddef gaus(x, a, x0, sigma):    return a*exp(-(x-x0)**2/(2*sigma**2))if __name__ == '__main__':    x = np.array([i for i in range(0, 100)])    y1 = gaus(x, 1, 50, 5)    y2 = gaus(x, 1, 45, 12)    fig = plt.figure()    ax = plt.axes(projection='3d')    ax.view_init(-90, 90)    ax.plot3D(x, y1, 100)    ax.plot3D(x, y2, 1)    plt.show()