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