这是一个矢量化的矢量，其依据是
np.searchsorted要追溯数组中每个键的位置，然后进行替换，请在这里原谅几乎是
性别歧视的 函数名（尽管无济于事）-
def replace_with_dict(ar, dic): # Extract out keys and values k = np.array(list(dic.keys())) v = np.array(list(dic.values())) # Get argsort indices sidx = k.argsort() # Drop the magic bomb with searchsorted to get the corresponding # places for a in keys (using sorter since a is not necessarily sorted). # Then trace it back to original order with indexing into sidx # Finally index into values for desired output. return v[sidx[np.searchsorted(k,ar,sorter=sidx)]]
样品运行-
In [82]: dic ={334:0, 4:22, 8:31, 12:16, 16:17, 24:27, 28:18, 32:21, 36:1} ...: ...: np.random.seed(0) ...: a = np.random.choice(dic.keys(), 20) ...:In [83]: aOut[83]: array([ 28, 16, 32, 32, 334, 32, 28, 4, 8, 334, 12, 36, 36, 24, 12, 334, 334, 36, 24, 28])In [84]: replace_with_dict(a, dic)Out[84]: array([18, 17, 21, 21, 0, 21, 18, 22, 31, 0, 16, 1, 1, 27, 16, 0, 0, 1, 27, 18])改善
对于大型数组，一种更快的方法是对值和键数组进行排序，然后
searchsorted不使用
sorter，就像这样-
def replace_with_dict2(ar, dic): # Extract out keys and values k = np.array(list(dic.keys())) v = np.array(list(dic.values())) # Get argsort indices sidx = k.argsort() ks = k[sidx] vs = v[sidx] return vs[np.searchsorted(ks,ar)]
运行时测试-
In [91]: dic ={334:0, 4:22, 8:31, 12:16, 16:17, 24:27, 28:18, 32:21, 36:1} ...: ...: np.random.seed(0) ...: a = np.random.choice(dic.keys(), 20000)In [92]: out1 = replace_with_dict(a, dic) ...: out2 = replace_with_dict2(a, dic) ...: print np.allclose(out1, out2)TrueIn [93]: %timeit replace_with_dict(a, dic)1000 loops, best of 3: 453 µs per loopIn [95]: %timeit replace_with_dict2(a, dic)1000 loops, best of 3: 341 µs per loop所有数组元素都不在字典中时的一般情况
如果不能保证输入数组中的所有元素都在字典中，则我们需要做一些工作，如下所示-
def replace_with_dict2_generic(ar, dic, assume_all_present=True): # Extract out keys and values k = np.array(list(dic.keys())) v = np.array(list(dic.values())) # Get argsort indices sidx = k.argsort() ks = k[sidx] vs = v[sidx] idx = np.searchsorted(ks,ar) if assume_all_present==0: idx[idx==len(vs)] = 0 mask = ks[idx] == ar return np.where(mask, vs[idx], ar) else: return vs[idx]
样品运行-
In [163]: dic ={334:0, 4:22, 8:31, 12:16, 16:17, 24:27, 28:18, 32:21, 36:1} ...: ...: np.random.seed(0) ...: a = np.random.choice(dic.keys(), (20)) ...: a[-1] = 400In [165]: aOut[165]: array([ 28, 16, 32, 32, 334, 32, 28, 4, 8, 334, 12, 36, 36, 24, 12, 334, 334, 36, 24, 400])In [166]: replace_with_dict2_generic(a, dic, assume_all_present=False)Out[166]: array([ 18, 17, 21, 21, 0, 21, 18, 22, 31, 0, 16, 1, 1, 27, 16, 0, 0, 1, 27, 400])
