1，列表

返回排序列表的索引

>>> lis = [1,2,3,0,1,9,8]
>>> sorted(range(len(lis)), key=lambda k: lis[k])
[3, 0, 4, 1, 2, 6, 5]
>>>

这个更简单

idx_sort = np.argsort(lis)

列表按照指定索引排序

idx_sort = np.argsort(lis)
np.array(mol_dic["conformers"])[idx_sort].tolist()

list补全

def pad_list(x):
    x += [0 for i in range(max(angle_group_num) - len(x))]
list(map(pad_list, labels))

map用法

zip 和 zip(*)用法

traindata = [(i,i,i) for i in range(8)]

traindata
# [(0, 0, 0),
#  (1, 1, 1),
#  (2, 2, 2),
#  (3, 3, 3),
#  (4, 4, 4),
#  (5, 5, 5),
#  (6, 6, 6),
#  (7, 7, 7)]

a,b,c = map(list, zip(*traindata))

a,b,c
# ([0, 1, 2, 3, 4, 5, 6, 7], [0, 1, 2, 3, 4, 5, 6, 7], [0, 1, 2, 3, 4, 5, 6, 7])

partial

from functools import partial

loader = DataLoader(dataset, batch_size=batchsize, 
                    collate_fn=partial(collate_new, max_num_atom=max_num_atom,
                                       wl_max_iter=wl_max_iter,
                                       data_enhancement = False))

def collate_new(data_list, max_num_atom, wl_max_iter, data_enhancement=True):
	#。。。。。。。
	return 。。。