| import numpy as np |
|
|
| |
| def weighted_random_sample(items: np.array, weights: np.array, n: int) -> np.array: |
| """ |
| Does np.random.choice but ensuring we don't have duplicates in the final result |
| |
| Args: |
| items (np.array): _description_ |
| weights (np.array): _description_ |
| n (int): _description_ |
| |
| Returns: |
| np.array: _description_ |
| """ |
| indices = np.arange(len(items)) |
| out_indices = [] |
|
|
| for _ in range(n): |
| chosen_index = np.random.choice(indices, p=weights) |
| out_indices.append(chosen_index) |
|
|
| mask = indices != chosen_index |
| indices = indices[mask] |
| weights = weights[mask] |
|
|
| if weights.sum() != 0: |
| weights = weights / weights.sum() |
|
|
| return items[out_indices] |
|
|
