使用生成器表達(dá)式的簡(jiǎn)單解決方案From PEP 289 Generator Expressions

Rationale

Experience with list comprehensions has shown their widespread utility

throughout Python. However, many of the use cases do not need to have a full list created in memory. Instead, they only need to iterate over the elements one at a time.

因?yàn)槟悴恍枰４嬷虚g結(jié)果

可能你有一個(gè)大的數(shù)據(jù)集

以及itertools標(biāo)準(zhǔn)庫(kù)模塊中的^{}，因?yàn)槟枰?jì)算數(shù)據(jù)集中每對(duì)有趣的點(diǎn)的距離。在$ cat euclid.py

from scipy.spatial.distance import euclidean

from itertools import combinations

lines = ['HETATM 1 H10 XSHQ 0 10.139 2.231 0.091 1.00 0.00 H',

'HETATM 2 N1 XSHQ 0 9.641 1.386 -0.104 1.00 0.00 N',

'HETATM 3 H9 XSHQ 0 9.773 1.133 -1.063 1.00 0.00 H',

'HETATM 4 C1 XSHQ 0 8.245 1.531 0.230 1.00 0.00 H']

H_lines = (line for line in lines if line[-1]=='H')

H_lists = (line.split() for line in H_lines)

H_data = ((int(tok[1]), [float(x) for x in tok[5:8]]) for tok in H_lists)

H_dist = {(i[0], j[0]):euclidean(i[1], j[1])

for i, j in combinations(H_data, 2)}

for m, n in H_dist:

print('Distance between points %d and %d is %.6f'%(

m, n, H_dist[m, n]))

$ python3 euclid.py

Distance between points 1 and 3 is 1.634404

Distance between points 1 and 4 is 2.023995

Distance between points 3 and 4 is 2.040842

$

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