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53 lines
1.1 KiB
Python
53 lines
1.1 KiB
Python
import logging
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from dataclasses import dataclass
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import numpy as np
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logging.basicConfig(level=logging.DEBUG)
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logger = logging.getLogger(__name__)
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@dataclass
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class Point:
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identifier: str
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weather: int
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is_weekend: bool
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is_game_on: bool
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sold: int = 0
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distance: int = 0
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@property
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def array(self):
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return np.array([self.weather, int(self.is_weekend), int(self.is_game_on)])
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def knn(point: Point, neighbours):
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for neighbour in neighbours:
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neighbour.distance = np.linalg.norm(point.array - neighbour.array)
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logger.debug(f"{neighbour.identifier}: {neighbour.distance}")
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return sorted(neighbours, key=lambda x: x.distance)[:K]
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neighbours = [
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Point("A", 5, True, False, 300),
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Point("B", 3, True, True, 225),
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Point("C", 1, True, False, 75),
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Point("D", 4, False, True, 200),
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Point("E", 4, False, False, 150),
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Point("F", 2, False, False, 50),
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]
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point = Point("T", 4, True, False)
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K = 4
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k_nearest = knn(point, neighbours)
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total = 0
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for n in k_nearest:
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total += n.sold
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average = total / K
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logger.debug(average)
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print(f"Number of loaves to make: {int(round(average, 0))}")
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