Problem p01354 - Generation 1

Orig Description

Problem F: The Castle
After successfully defeating the enemy who was lying in wait, the rabbit was able to lead the hero into the enemy's castle. After freeing the cats who were trapped in the castle's underground dungeon, some of them agreed to help the hero using their own abilities.
According to the cats, the hero must pass through the first n rooms in order to reach the demon king who is located deep within the castle. However, there is an enemy waiting in each room and they must be defeated one by one in order to proceed. For each of the m cats who have become allies, the success rate for defeating each enemy in each room is known. The hero will send the cats one by one toward the back of the castle. Since each room cannot be passed through until the enemy within it is defeated, if a cat is defeated by an enemy in a certain room, the next cat will have to fight that enemy.
The dispatched cat will advance until it is defeated by the enemy, but it is possible to determine which enemy defeated the dispatched cat each time, allowing the hero to decide which cat to send next. How can the probability of defeating all the enemies that the cats will face be maximized?
Input
The first line of the input contains two integers, m and n, separated by a space. 1 ≤ m, n ≤ 16.
Following that, m lines are given. Each line contains n real numbers representing the probability that a cat will win against the enemy. The j-th real number on the i+1-th line represents the probability of winning against the enemy in the j-th room. Probabilities are given up to three decimal places.
Output
Determine the optimal order of cats such that the probability of defeating all the enemies that the cats will face is maximized, and output that probability. The output may contain an error, but the error should be within 10-9 of the true value.
Sample Input 1
2 3
0.900 0.500 0.100
0.500 0.500 0.500
Sample Output 1
0.372500000000

Extracted Specification

Canonicalized Input Description:

An integer m (1 ≤ m ≤ 16), representing some quantity or size.
An integer n (1 ≤ n ≤ 16), representing some quantity or size.
A list of m lists, each containing n real numbers representing probabilities, given up to three decimal places.

### Example Input:

```
2 3
0.900 0.500 0.100
0.500 0.500 0.500
```

### Function Signature:
Write a function f(m, n, probabilities) that takes in the input.
```python
def f(m: int, n: int, probabilities: List[List[float]]):
    '''
    m: an integer
    n: an integer
    probabilities: a list of lists of real numbers
    '''
```

Test Case Generator

Sure, here's a Python test case generator for the given problem statement "The Castle":

```python
import random

def tcgen():
    # Generate m and n
    m = random.randint(1, 16)
    n = random.randint(1, 16)
    
    # Generate the probabilities
    probabilities = [[round(random.uniform(0, 1), 3) for _ in range(n)] for _ in range(m)]
    
    return m, n, probabilities

# Function to print the generated test case in the appropriate format
def print_test_case(m, n, probabilities):
    print(m, n)
    for row in probabilities:
        print(" ".join(f"{p:.3f}" for p in row))

# Generate a test case
m, n, probabilities = tcgen()
print_test_case(m, n, probabilities)
```

This script generates random test cases for the problem "The Castle". Here's a breakdown of what it does:

1. It first generates random values for `m` and `n` within the given constraints (1 ≤ m, n ≤ 16).
2. It then creates a list of lists to store the probabilities that each cat (up to `m` cats) has of defeating each enemy in the rooms (up to `n` rooms). Probabilities are randomly chosen real numbers between 0 and 1, rounded to 3 decimal places.
3. The `print_test_case` function formats the generated test case appropriately for input to the problem.

To use this test case generator, you can simply call the `tcgen` function, and it will return `m`, `n`, and the `probabilities` list. You can then use the `print_test_case` function to print these values in the desired format.

Extract Arguments

def extract_arguments(fh):
    m, n = map(int, fh.readline().strip().split())
    probabilities = []
    for _ in range(m):
        probabilities.append(list(map(float, fh.readline().strip().split())))
    return m, n, probabilities