matplotlib-从轮廓线提取数据 [英] matplotlib - extracting data from contour lines

问题描述

我想从均匀分布的2D数据(类似图像的数据)的单个轮廓中获取数据.

I would like to get data from a single contour of evenly spaced 2D data (an image-like data).

基于在类似问题中找到的示例:如何获取绘制线的(x，y)值通过等高线图(matplotlib)?

Based on the example found in a similar question: How can I get the (x,y) values of the line that is ploted by a contour plot (matplotlib)?

>>> import matplotlib.pyplot as plt
>>> x = [1,2,3,4]
>>> y = [1,2,3,4]
>>> m = [[15,14,13,12],[14,12,10,8],[13,10,7,4],[12,8,4,0]]
>>> cs = plt.contour(x,y,m, [9.5])
>>> cs.collections[0].get_paths()

此呼叫cs.collections[0].get_paths()的结果是:

[Path([[ 4.          1.625     ]
 [ 3.25        2.        ]
 [ 3.          2.16666667]
 [ 2.16666667  3.        ]
 [ 2.          3.25      ]
 [ 1.625       4.        ]], None)]

基于绘图，此结果有意义，并且似乎是轮廓线的(y，x)对的集合.

Based on the plots, this result makes sense and appears to be collection of (y,x) pairs for the contour line.

除了手动循环返回值，提取坐标和装配线的数组之外，还有更好的方法从matplotlib.path对象取回数据吗?从matplotlib.path提取数据时是否有陷阱要注意?

Other than manually looping over this return value, extracting the coordinates and assembling arrays for the line, are there better ways to get data back from a matplotlib.path object? Are there pitfalls to be aware of when extracting data from a matplotlib.path?

或者，在matplotlib或更好的numpy/scipy中是否有替代品可以做类似的事情?理想的做法是获得一个描述这条线的(x，y)对的高分辨率矢量，该矢量可以用于进一步的分析，因为通常我的数据集并不像上面的示例那样小或简单.

Alternatively, are there alternatives within matplotlib or better yet numpy/scipy to do a similar thing? Ideal thing would be to get a high resolution vector of (x,y) pairs describing the line, which could be used for further analysis, as in general my datasets are not a small or simple as the example above.

推荐答案

对于给定的路径，您可以得到如下几点:

For a given path, you can get the points like this:

p = cs.collections[0].get_paths()[0]
v = p.vertices
x = v[:,0]
y = v[:,1]

这篇关于matplotlib-从轮廓线提取数据的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！