开发笔记:如何标记和分组数组中的唯一功能

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方法＃1：这是一种方法 -

def label_based_on_shifts(a):
# Detect starts of each label(element is non-zero and is different
# from the previous element)
mask = np.r_[a[0]!=0,(a[1:] != a[:-1]) & (a[1:] !=0)]
# Setup id array, which when cumulatively summed would lead us to
# labelled islands
out = mask.astype(np.uint64).cumsum()
# Set the islands that are zeros in input array to be zeros in o/p too
out[a==0] = 0
return out


样品运行 -

In [53]: a
Out[53]: array([0, 0, 1, 1, 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 0, 0])
In [54]: label_based_on_shifts(a)
Out[54]: array([0, 0, 1, 1, 0, 0, 2, 2, 3, 3, 4, 4, 5, 5, 0, 0])


方法＃2：另一个用np.cumsum取代np.repeat -

def label_based_on_shifts_v2(a):
mask = np.r_[True,(a[1:] != a[:-1]),True]
idx = np.flatnonzero(mask)
valid_idx_mask = a[idx[:-1]]!=0
starts = idx[:-1][valid_idx_mask]
stops = idx[1:][valid_idx_mask]
lens = stops-starts
out = np.zeros(len(a), dtype=int)
out[a!=0] = np.repeat(np.arange(1,len(starts)+1), lens)
return out