posts: reservoir-sampling: add k-element sampling

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Bruno BELANYI 2024-08-02 21:10:39 +01:00
parent b5d3086542
commit d9daa68902

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@ -81,3 +81,65 @@ probability $\frac{1}{N} \cdot \frac{N}{N + 1} = \frac{1}{N + 1}$ of being the
element.
And thus, we have proven $H_{N + 1}$ at the end of the loop.
## Sampling $k$ element
The code for sampling $k$ elements is very similar to the one-element case.
```python
def sample[T](stream: Iterable[T], k: int = 1) -> list[T]:
stream_iter = iter(stream)
# Retain the first 'k' elements in the reservoir
res = list(itertools.islice(stream_iter, k))
for i, val in enumerate(stream_iter, start=k):
j = random.randint(0, i)
# Replace one element at random with probability k/(i + 1)
if j < k:
res[j] = val
# Return 'k' randomly sampled elements
return res
```
### Proof
Let us once again do a proof by induction, assuming the stream contains at least
$k$ items.
#### Hypothesis $H_N$
After iterating through the first $N$ items in the stream, each of them has had
an equal $\frac{k}{N}$ probability of being sampled from the stream.
#### Base Case $H_k$
We can trivially observe that the first $k$ element are sampled at the start of
the algorithm, $\frac{k}{k} = 1$, the hypothesis has been verified.
#### Inductive Case
For a given $N$, let us assume that $H_N$ holds. Let us now look at the events
of the loop iteration where `i = N`, in order to prove $H_{N + 1}$.
`j = random.randint(0, i)` uniformly selects a value in the range $[0, i]$,
a.k.a $[0, N]$. We then have three cases:
* `j >= k`, with probability $1 - \frac{k}{N + 1}$: we do not modify the
sampled reservoir at all.
* `j < k`, with probability $\frac{k}{N + 1}$: we sample the new element to
replace the `j`-th element of the reservoir. Therefore for any element
$e \in [0, k[$ we can either have:
* $j = e$: the element _is_ replaced, probability $\frac{1}{k}$.
* $j \neq e$: the element is _not_ replaced, probability $\frac{k - 1}{k}$.
We can now compute the probability that a previously sampled element is kept in
the reservoir:
$1 - \frac{k}{N + 1} + \frac{k}{N + 1} \cdot \frac{k - 1}{k} = \frac{N}{N + 1}$.
By $H_N$, any of the first $N$ elements had a $\frac{k}{N}$ probability
of being sampled before at the start of the loop, each element now has a
probability $\frac{k}{N} \cdot \frac{N}{N + 1} = \frac{k}{N + 1}$ of being the
element.
We have now proven that all elements have a probability $\frac{k}{N + 1}$ of
being sampled at the end of the loop, therefore $H_{N + 1}$ has been verified.