要从未确定大小的数组中检索 k 随机数,我们使用称为水库采样的技术。任何人都可以通过示例代码简要介绍它是如何发生的吗?
答案 0 :(得分:31)
我实际上并没有意识到这有一个名字,所以我从头开始证明并实施了这个:
import random
def random_subset( iterator, K ):
result = []
N = 0
for item in iterator:
N += 1
if len( result ) < K:
result.append( item )
else:
s = int(random.random() * N)
if s < K:
result[ s ] = item
return result
接近结尾的证据。
答案 1 :(得分:8)
按照Knuth(1981)的描述,储层采样(算法R)可以实现如下:
import random
def sample(iterable, n):
"""
Returns @param n random items from @param iterable.
"""
reservoir = []
for t, item in enumerate(iterable):
if t < n:
reservoir.append(item)
else:
m = random.randint(0,t)
if m < n:
reservoir[m] = item
return reservoir
答案 2 :(得分:1)
爪哇
import java.util.Random;
public static void reservoir(String filename,String[] list)
{
File f = new File(filename);
BufferedReader b = new BufferedReader(new FileReader(f));
String l;
int c = 0, r;
Random g = new Random();
while((l = b.readLine()) != null)
{
if (c < list.length)
r = c++;
else
r = g.nextInt(++c);
if (r < list.length)
list[r] = l;
b.close();}
}
答案 3 :(得分:0)
Python解决方案
import random
class RESERVOIR_SAMPLING():
def __init__(self, k=1000):
self.reservoir = []
self.k = k
self.nb_processed = 0
def add_to_reservoir(self, sample):
self.nb_processed +=1
if(self.k >= self.nb_processed):
self.reservoir.append(sample)
else:
#randint(a,b) gives a<=int<=b
j = random.randint(0,self.nb_processed-1)
if(j < k):
self.reservoir[j] = sample
k = 10
samples = [i for i in range(10)] * k
res = RESERVOIR_SAMPLING(k)
for sample in samples:
res.add_to_reservoir(sample)
print(res.reservoir)
out[1]: [9, 8, 4, 8, 3, 5, 1, 7, 0, 9]