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https://github.com/onyx-and-iris/grokking-algorithms.git
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85 lines
2.0 KiB
Python
85 lines
2.0 KiB
Python
import logging
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from dataclasses import dataclass
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from tabulate import tabulate
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logging.basicConfig(
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level=logging.DEBUG,
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format="%(asctime)s %(levelname)s\n\r%(message)s",
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datefmt="%H:%M:%S",
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)
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logger = logging.getLogger(__name__)
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@dataclass
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class Item:
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name: str
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priority: int
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weight: int
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def dynamic(items, n):
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# create table and zero fill it (required for calculations)
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table = [[0 for _ in range(W + 1)] for _ in range(n + 1)]
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# calculate all possible max values for items in knapsack
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for i in range(1, n + 1):
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for w in range(1, W + 1):
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if items[i - 1].weight <= w:
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table[i][w] = max(
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items[i - 1].priority + table[i - 1][w - items[i - 1].weight],
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table[i - 1][w],
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)
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else:
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table[i][w] = table[i - 1][w]
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format_and_print(table)
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return get_items_in_knapsack(table[-1][-1], items, n, table)
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def format_and_print(table):
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# enumerate first row (headings) + label each row in column0
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for i, row in enumerate(table):
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if i == 0:
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continue
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row[0] = items[i - 1].name
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table[0] = [None, *[i for i in range(1, W + 1)]]
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# print tabularised 2D array
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logger.info([item.name for item in items])
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logger.info(tabulate(table, tablefmt="pretty"))
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def get_items_in_knapsack(highest_value, items, n, table):
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in_knapsack = []
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w = W
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res = highest_value
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for i in range(n, 0, -1):
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if res <= 0:
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break
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if res == table[i - 1][w]:
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continue
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else:
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in_knapsack.append(items[i - 1].name)
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res = res - items[i - 1].priority
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w = w - items[i - 1].weight
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return in_knapsack
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items = [
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Item("Water", 10, 3),
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Item("Book", 3, 1),
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Item("Food", 9, 2),
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Item("Jacket", 5, 2),
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Item("Camera", 6, 1),
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]
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W = 6
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in_knapsack = dynamic(items, len(items))
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print(f"Knapsack contains: {in_knapsack}")
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