查找坐标数组的角点 [英] Finding the Corners of the an array of coordinates

问题描述

我在 Numpy 中有一个二维坐标数组.

I have a 2D array of Coordinates in Numpy.

我的目标是尝试找到角落(好像它是一个正方形).所以:

My goal is to attempt to find the corners (as if it were a square). So the :

左上:最小的x，最大的y右上角:最大的 x，最大的 y左下:最小的 x，最小的 y右下:最大的x，最小的y

Top left: smallest x, highest y Top right: largest x, largest y bottom left: smallest x, smallest y bottom right: largest x, smallest y

显然，这些对中的每一个都需要考虑其他值.

Obviously each of these pairs need to consider the other values.

我试图根据行取最小值和最大值:

I was trying to take the min and max depending on the row:

        BottomLeft = np.min(np.min(hull, axis=1), axis=0)

然而，这并不能将这对值保持在一起.它必须是最小可能的 X 值，以及其中最小的 y 值.或者类似的东西.我假设有一种有效的方法可以用 numpy 做到这一点?

However, this does not keep the pair of values together. It would have to be something like the smallest possible X values, and out of those, the smallest y value. Or something along these lines. I am assuming there is efficient way to do this with numpy?

这是一个数据示例:

    [[[260 156]]

 [[248 176]]

 [[235 197]]

 [[233 199]]

 [[192 199]]

 [[174 197]]

 [[160 171]]

 [[150 151]]

 [[154 149]]

 [[156 149]]

 [[260 151]]]

谢谢！

推荐答案

假设x坐标如下

x = np.arange(0, 22, 2)

并假设y坐标如下

y = np.arange(20, 32, 2)

xx, yy = np.meshgrid(x, y)

yy = np.flip(yy, 0)

print(xx)

print(yy)

然后你可以对 xx 和 yy 做任何操作，因为它们是坐标.

Then you can do whatever operation with xx and yy as they are coordinates.

例如

让我们假设 z 是海拔

let us assume z is the elevation

z = np.random.randint(2, high=20, size=(yy.shape[0], yy.shape[1])) # xx can also be used


import matplotlib.pyplot as plt 

plt.contourf(xx, yy, z)
plt.colorbar()

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