类似于scipy.interpolate.griddata? [英] analogy to scipy.interpolate.griddata?

问题描述

我想对给定的3D点云进行插值:

I want to interpolate a given 3D point cloud:

我查看了scipy.interpolate.griddata，结果正是我所需要的，但是据我了解，我需要输入"griddata"，其含义类似于x = [[0,0,0],[1,1,1],[2,2,2]].

I had a look at scipy.interpolate.griddata and the result is exactly what I need, but as I understand, I need to input "griddata" which means something like x = [[0,0,0],[1,1,1],[2,2,2]].

但是我给定的3D点云没有这种网格外观-x，y值的行为不像网格-无论如何，每个x，y值只有一个z值.*

But my given 3D point cloud don't has this grid-look - The x,y-values don't behave like a grid - anyway there is only a single z-value for each x,y-value.*

那么对于不在网格点云中的scipy.interpolate.griddata，还有其他替代方法吗?

So is there an alternative to scipy.interpolate.griddata for my not-in-a-grid-point-cloud?

* 无网格外观"表示我的输入看起来像这样:

*edit: "no grid look" means my input looks like this:

x = [0,4,17]
y = [-7,25,116]
z = [50,112,47]

推荐答案

这是我用于此类操作的函数:

This is a function I use for this kind of stuff:

from numpy import linspace, meshgrid

def grid(x, y, z, resX=100, resY=100):
    "Convert 3 column data to matplotlib grid"
    xi = linspace(min(x), max(x), resX)
    yi = linspace(min(y), max(y), resY)
    Z = griddata(x, y, z, xi, yi)
    X, Y = meshgrid(xi, yi)
    return X, Y, Z

然后像这样使用它:

  X, Y, Z = grid(x, y, z)

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