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我在(x,y)平面和(x,y,z)平面中有一个随机漫步器和一个-log(双变量高斯)。这两个数据集基本上是独立的。Python,Matplotlib:在3D图中绘制垂直线,当数据是独立的时
我想抽样,比如5(x,y)对的随机游走者,在z轴上画垂直线,当它“符合”双变量高斯时终止垂直线。
这是我到目前为止的代码:
import matplotlib as mpl
import matplotlib.pyplot as plt
import random
import numpy as np
import seaborn as sns
import scipy
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.mlab import bivariate_normal
%matplotlib inline
# Data for random walk
def randomwalk():
mpl.rcParams['legend.fontsize'] = 10
xyz = []
cur = [0, 0]
for _ in range(40):
axis = random.randrange(0, 2)
cur[axis] += random.choice([-1, 1])
xyz.append(cur[:])
# Get density
x, y = zip(*xyz)
data = np.vstack([x,y])
kde = scipy.stats.gaussian_kde(data)
density = kde(data)
# Data for bivariate gaussian
a = np.linspace(-7.5, 7.5, 40)
b = a
X,Y = np.meshgrid(a, b)
Z = bivariate_normal(X, Y)
surprise_Z = -np.log(Z)
# Get random points from walker and plot up z-axis to the gaussian
M = data[:,np.random.choice(20,5)].T
# Plot figure
fig = plt.figure(figsize=(10, 7))
ax = fig.gca(projection='3d')
ax.plot(x, y, 'grey', label='Random walk') # Walker
ax.scatter(x[-1], y[-1], c='k', marker='o') # End point
ax.legend()
surf = ax.plot_surface(X, Y, surprise_Z, rstride=1, cstride=1,
cmap = plt.cm.gist_heat_r, alpha=0.1, linewidth=0.1)
#fig.colorbar(surf, shrink=0.5, aspect=7, cmap=plt.cm.gray_r)
for i in range(5):
ax.plot([M[i,0], M[i,0]],[M[i,1], M[i,1]], [0,10],'k--',alpha=0.8, linewidth=0.5)
ax.set_zlim(0, 50)
ax.set_xlim(-10, 10)
ax.set_ylim(-10, 10)
将会产生
正如你可以看到我用的是如何当他们终止垂直线挣扎的唯一的事情满足适当的Z值。任何想法都欢迎!
这是令人沮丧的简单。我发誓我尝试了类似的东西。但是,谢谢! – TMorville