plot_surface 的数组应该如何构建?

问题描述

我试图了解如何构建用于plot_surface(在Axes3d中)的数组.我试图构建一个简单的表面处理这些数组的数据:

I'm trying to understand how to build arrays for use in plot_surface (in Axes3d).I tried to build a simple surface manipulating data of those arrays:

In [106]: x
Out[106]:
array([[0, 0],
       [0, 1],
       [0, 0]])

In [107]: y
Out[107]:
array([[0, 0],
       [1, 1],
       [0, 0]])

In [108]: z
Out[108]:
array([[0, 0],
       [1, 1],
       [2, 2]])

但是我无法弄清楚它们是如何解释的-例如，在我的绘图中z = 2中没有任何内容.任何人都请确切说明将取哪些值作为指向点，取哪些值作为线并最终取曲面.

But I can't figure out how they are interpreted - for example there is nothing in z=2 on my plot.Anybody please explain exactly which values will be taken to make point, which for line and finally surface.

例如，我想构建一个与线点连接的表面:[0,0,0]-> [1,1,1]-> [0,0,2][0,0,0]->[1,-1,1]->[0,0,2]以及这些线之间的表面.plot_surface 的数组应该是什么样的?

For example I would like to build a surface that would connect with lines points:[0,0,0]->[1,1,1]->[0,0,2][0,0,0]->[1,-1,1]->[0,0,2]and a surface between those lines.What should arrays for plot_surface look like to get something like this?

推荐答案

了解 plot_surface 中的网格如何工作并不容易.因此，首先我将给出一个一般性的解释，然后再解释如何根据您的情况转换数据.如果您有一个 N x个值的数组和一个 M 个y值的数组，则需要创建两个维度为(M，N) 每个.幸运的是 numpy.meshgrid 将有所帮助.使困惑?看一个例子:

Understanding how the grids in plot_surface work is not easy. So first I'll give a general explanation, and then I'll explain how to convert the data in your case.If you have an array of N x values and an array of M y values, you need to create two grids of x and y values of dimension (M,N) each. Fortunately numpy.meshgrid will help. Confused? See an example:

x = np.arange(3)
y=np.arange(1,5)
X, Y = np.meshgrid(x,y)

元素(x [i]，y [j])作为(X [j，i]，Y [j，i])访问.而它的Z值当然是Z[j,i]，你也需要定义.

The element (x[i], y[j]) is accessed as (X[j,i], Y[j,i]). And its Z value is, of course, Z[j,i], which you also need to define.

话虽如此，您的数据确实按预期在(0,0,2)中产生了曲面的一个点.事实上，在那个位置有两个点，来自坐标索引(0,0,0)和(1,1,1).

Having said that, your data does produce a point of the surface in (0,0,2), as expected. In fact, there are two points at that position, coming from coordinate indices (0,0,0) and (1,1,1).

我附上绘制数组的结果:

I attach the result of plotting your arrays with:

fig = plt.figure()
ax=fig.add_subplot(1,1,1, projection='3d')
surf=ax.plot_surface(X, Y, Z)

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