您可以子类化
np.s_以支持“矢量化”切片符号：
import numpy as npimport typesclass Block_Slice(np.lib.index_tricks.Indexexpression): @staticmethod def expand_slice(slice_, result_type=types.GeneratorType, force_type=False): bc = np.broadcast(slice_.start, slice_.stop, slice_.step) if bc.size == 1 and not force_type: return slice_ if result_type in ('generator', types.GeneratorType): return (slice(*idx) for idx in bc) result_type = tuple if result_type=='tuple' else result_type return result_type(slice(*idx) for idx in bc) def __getitem__(self, item): if isinstance(item, slice): item = self.expand_slice(item, tuple) elif isinstance(item, tuple): item = tuple(j for i in item for j in (self.expand_slice(i, force_type=True) if isinstance(i, slice) else (i,))) return super().__getitem__(item)bs_ = Block_Slice(maketuple=False)a = sum(np.ogrid[:2000:1000, :300:100, :40:10, :6])left = [1, 0, 0]right = [2, 2, 4]a[bs_[left:right]]# array([[[[1000, 1001, 1002, 1003, 1004, 1005],# [1010, 1011, 1012, 1013, 1014, 1015],# [1020, 1021, 1022, 1023, 1024, 1025],# [1030, 1031, 1032, 1033, 1034, 1035]],# [[1100, 1101, 1102, 1103, 1104, 1105],# [1110, 1111, 1112, 1113, 1114, 1115],# [1120, 1121, 1122, 1123, 1124, 1125],# [1130, 1131, 1132, 1133, 1134, 1135]]]])a[bs_[..., range(3):5]]# array([[[[ 12, 13, 14],# [ 22, 23, 24],# [ 32, 33, 34]],# [[ 112, 113, 114],# [ 122, 123, 124],# [ 132, 133, 134]],# [[ 212, 213, 214],# [ 222, 223, 224],# [ 232, 233, 234]]],# [[[1012, 1013, 1014],# [1022, 1023, 1024],# [1032, 1033, 1034]],# [[1112, 1113, 1114],# [1122, 1123, 1124],# [1132, 1133, 1134]],# [[1212, 1213, 1214],# [1222, 1223, 1224],# [1232, 1233, 1234]]]])a[bs_[:right, [4, 2, 1]]]# array([[[[ 4, 2, 1],# [ 14, 12, 11],# [ 24, 22, 21],# [ 34, 32, 31]],# [[ 104, 102, 101],# [ 114, 112, 111],# [ 124, 122, 121],# [ 134, 132, 131]]],# [[[1004, 1002, 1001],# [1014, 1012, 1011],# [1024, 1022, 1021],# [1034, 1032, 1031]],# [[1104, 1102, 1101],# [1114, 1112, 1111],# [1124, 1122, 1121],# [1134, 1132, 1131]]]])
