根据接近度从2D numpy数组中删除元素

debugcn 发表于 Dev

错误不是

我有以下形状的ndarray：

[[5 2][6 2][10 2][10 10]]

这些是XY坐标。如何遍历此数组并删除所有2D（欧几里德距离）中比当前阈值更接近当前元素的所有后续元素？例如，我将距离阈值设置为1，我将得到以下数组

[[5 2][10 2][10 10]]

[6 2]将被删除，因为它比阈值（1）更近。

真实数据：

array([[ 25, 478],
   [ 26, 366],
   [ 26, 478],
   [ 27, 183],
   [ 28, 367],
   [ 28, 477],
   [ 29, 477],
   [ 43, 374],
   [ 44, 374],
   [ 45, 374],
   [ 46, 374],
   [ 47, 374],
   [ 47, 375],
   [ 57,  82],
   [ 58, 133],
   [ 60,  25],
   [ 86, 445],
   [ 89, 226],
   [ 89, 227],
   [ 89, 228],
   [ 89, 229],
   [ 89, 230],
   [ 96, 286],
   [105, 404],
   [106, 404],
   [107, 403],
   [108, 403],
   [117, 355],
   [119, 355],
   [121,  43],
   [122,  42],
   [122,  43],
   [122, 127],
   [122, 490],
   [123, 489],
   [123, 490],
   [137, 438],
   [138, 437],
   [151, 229],
   [162, 149],
   [163, 326],
   [188, 465],
   [188, 466],
   [189, 115],
   [189, 116],
   [218, 291],
   [230, 174],
   [230, 175],
   [230, 176],
   [230, 177],
   [231, 173],
   [231, 174],
   [231, 175],
   [231, 176],
   [231, 177],
   [231, 178],
   [240,  33],
   [241,  33],
   [242,  34],
   [249, 118],
   [250, 256],
   [260, 208],
   [260, 209],
   [260, 210],
   [274, 372],
   [277,  39],
   [302, 216],
   [302, 217],
   [302, 218],
   [302, 219],
   [302, 220],
   [302, 221],
   [302, 222],
   [302, 223],
   [315, 325],
   [322, 258],
   [322, 259],
   [341, 172],
   [346, 457],
   [359, 388],
   [360, 389],
   [361, 390],
   [386, 307],
   [392, 372],
   [393, 136],
   [393, 360],
   [393, 374],
   [394, 134],
   [394, 135],
   [394, 136],
   [394, 137],
   [394, 138],
   [394, 139],
   [394, 140],
   [394, 141],
   [394, 142],
   [394, 143],
   [394, 144],
   [409, 266],
   [437, 132],
   [439, 131],
   [467, 100],
   [471, 236],
   [472, 235],
   [474, 234],
   [479, 104]])

奥利弗·W。

在列表中进行迭代，同时从中删除元素是一种不好的做法，因为这会导致无法预料的结果。因此，我认为调用一个函数并从该函数返回一个新列表更加清楚。

def reduce_tail(l, index, threshold=1):
    elm = l[index]
    mask = np.linalg.norm(elm-l, axis=1) > threshold
    mask[:index+1] = True  #ensure to return the head of the array unchanged
    return l[mask]

def my_reduce(z, threshold=1):
    z = np.array(z)
    index = 0
    while True:
        z = reduce_tail(z, index, threshold)
        index += 1
        if index == z.shape[0]:
            break
    return z.tolist()

演示：

>>> z = [[5, 2],[6, 2],[5,1],[10, 2],[10, 10]]
>>> x = [[5, 2],[6, 2],[6,3],[10, 2],[10, 10]]
>>> l = [[5, 2],[6, 2],[10, 2],[10, 10]]
>>> my_reduce(l)
[[5, 2], [10, 2], [10, 10]]
>>> my_reduce(x)
[[5, 2], [6, 3], [10, 2], [10, 10]]
>>> my_reduce(z)
[[5, 2], [10, 2], [10, 10]]
>>>

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