from dataclasses import dataclass
from operator import attrgetter
@dataclass
class Item:
weight: int
value: int
@property
def ratio(self) -> float:
"""
Return the value-to-weight ratio for the item.
Returns:
float: The value-to-weight ratio for the item.
Examples:
>>> Item(10, 65).ratio
6.5
>>> Item(20, 100).ratio
5.0
>>> Item(30, 120).ratio
4.0
"""
return self.value / self.weight
def fractional_cover(items: list[Item], capacity: int) -> float:
"""
Solve the Fractional Cover Problem.
Args:
items: A list of items, where each item has weight and value attributes.
capacity: The maximum weight capacity of the knapsack.
Returns:
The maximum value that can be obtained by selecting fractions of items to cover
the knapsack's capacity.
Raises:
ValueError: If capacity is negative.
Examples:
>>> fractional_cover((Item(10, 60), Item(20, 100), Item(30, 120)), capacity=50)
240.0
>>> fractional_cover([Item(20, 100), Item(30, 120), Item(10, 60)], capacity=25)
135.0
>>> fractional_cover([Item(10, 60), Item(20, 100), Item(30, 120)], capacity=60)
280.0
>>> fractional_cover(items=[Item(5, 30), Item(10, 60), Item(15, 90)], capacity=30)
180.0
>>> fractional_cover(items=[], capacity=50)
0.0
>>> fractional_cover(items=[Item(10, 60)], capacity=5)
30.0
>>> fractional_cover(items=[Item(10, 60)], capacity=1)
6.0
>>> fractional_cover(items=[Item(10, 60)], capacity=0)
0.0
>>> fractional_cover(items=[Item(10, 60)], capacity=-1)
Traceback (most recent call last):
...
ValueError: Capacity cannot be negative
"""
if capacity < 0:
raise ValueError("Capacity cannot be negative")
total_value = 0.0
remaining_capacity = capacity
for item in sorted(items, key=attrgetter("ratio"), reverse=True):
if remaining_capacity == 0:
break
weight_taken = min(item.weight, remaining_capacity)
total_value += weight_taken * item.ratio
remaining_capacity -= weight_taken
return total_value
if __name__ == "__main__":
import doctest
if result := doctest.testmod().failed:
print(f"{result} test(s) failed")
else:
print("All tests passed")