将NumPy 2D阵列中的所有2D点连接为三角形网格

时间:2014-07-03 13:34:17

标签: python arrays numpy matplotlib

我对Python很陌生,我试图绘制一个像这样的三角形网格:

import matplotlib.pyplot as plt
import numpy as np

r   = 0.25
d   = 2*r
s   = 0

l1 = np.array([[s,0], [s+d,0], [s+2*d,0], [s+3*d,0]]) 
l2 = np.array([[s-r,d], [s+r,d], [s+r+d,d], [s+r+2*d,d]])
l3 = np.array([[s,2*d], [s+d,2*d], [s+2*d,2*d], [s+3*d,2*d]])
l4 = np.array([[s-r,3*d], [s+r,3*d], [s+r+d,3*d], [s+r+2*d,3*d]])
l5 = np.array([[s,4*d], [s+d,4*d], [s+2*d,4*d], [s+3*d,4*d]])

plt.scatter(*zip(*l1))
plt.scatter(*zip(*l2))
plt.scatter(*zip(*l3))
plt.scatter(*zip(*l4))
plt.scatter(*zip(*l5))

plt.show

我的问题是,我没有真正的线索如何连接所有点。我为所有plt.plot(*zip(*l1))添加了l的水平线,但我不知道如何绘制'垂直'之字形线......任何人都很简单'溶液

非常感谢提前!

2 个答案:

答案 0 :(得分:1)

按照您的方式使用代码(否则根据您想要的内容查看triplot_demo,如@GBy所述),您可以提取或旋转每个数组,以便您只是向下绘制线条:

import matplotlib.pyplot as plt
import numpy as np

r   = 0.25
d   = 2*r
s   = 0

l1 = np.array([[s,0], [s+d,0], [s+2*d,0], [s+3*d,0]])
l2 = np.array([[s-r,d], [s+r,d], [s+r+d,d], [s+r+2*d,d]])
l3 = np.array([[s,2*d], [s+d,2*d], [s+2*d,2*d], [s+3*d,2*d]])
l4 = np.array([[s-r,3*d], [s+r,3*d], [s+r+d,3*d], [s+r+2*d,3*d]])
l5 = np.array([[s,4*d], [s+d,4*d], [s+2*d,4*d], [s+3*d,4*d]])

fig = plt.figure(0)
ax = fig.add_subplot(111)

larr = [l1,l2,l3,l4,l5]

# Plot horizontally
for l in larr:

  # same as your *zip(*l1), but you can select on a column-wise basis
  ax.errorbar(l[:,0], l[:,1], fmt="o", ls="-", color="black")

# Plot zig-zag-horizontally
for i in range(len(larr[0])):

  lxtmp = np.array([x[:,0][i] for x in larr])
  lytmp = np.array([x[:,1][i] for x in larr])

  ax.errorbar(lxtmp, lytmp, fmt="o", ls="-", color="black")

ax.set_ylim([-0.1,2.1])
ax.set_xlim([-0.6,1.6])

plt.show()

plot image

编辑:

lxtmp = np.array([x[:,0][i] for x in larr])

所以,x [:,0]表示占用所有行":"但只有第一列" 0"。对于l1,它将返回:

l1[:,0]
array([ 0. ,  0.5,  1. ,  1.5])

是l1的x值。执行l1 [:,1]将返回列" 1"中的所有行,即y值。要绘制垂直线,您需要从每个第i个数组中获取所有x和y值,因此您将遍历所有数组,取出第i个元素。例如,第3个垂直之字形线将是:

lxtmp = [l1[:,0][2], l2[:,0][2], l3[:,0][2], l4[:,0][2], l5[:,0][2]]
lytmp = [l1[:,1][2], l2[:,1][2], l3[:,1][2], l4[:,1][2], l5[:,1][2]]

为了简化和运行每个元素,我创建了' larr'循环和建立'然后以正常的python方式,例如,

[i for i in range(1,10)]
[1, 2, 3, 4, 5, 6, 7, 8, 9]

答案 1 :(得分:1)

triplot就是为了这个目的而制作的:绘制三角形。 您可以只传递xy坐标(在这种情况下将计算Delaunay三角剖分),或者可以指定自己的三角形的完整Triangulation对象。

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.tri as mtri

r = 0.25
d = 2*r
s = 0

def meshgrid_triangles(n, m):
    """ Returns triangles to mesh a np.meshgrid of n x m points """
    tri = []
    for i in range(n-1):
        for j in range(m-1):
            a = i + j*(n)
            b = (i+1) + j*n
            d = i + (j+1)*n
            c = (i+1) + (j+1)*n
            if j%2 == 1:
                tri += [[a, b, d], [b, c, d]]
            else:
                tri += [[a, b, c], [a, c, d]]
    return np.array(tri, dtype=np.int32)


x0 = np.arange(4) * d
y0 = np.arange(5) * d
x, y = np.meshgrid(x0, y0)
x[1::2] -= r
triangles = meshgrid_triangles(4, 5)
triangulation = mtri.Triangulation(x.ravel(), y.ravel(), triangles)
plt.scatter(x, y, color='red')
plt.triplot(triangulation, 'g-h')

plt.show()

enter image description here