How to implement key validation with negative and matching values for mirror points?

To verify keys with negative and matching values in a task with mirror points, you can use the following approach:

1. Identify mirror points: Usually, mirror points are pairs of values that are mirror reflections of each other, for example, (x, y) and (-x, y).

2. Check keys: If the keys are coordinates or features, consider that for mirror points, some coordinate values may be negative or identical.

3. Verification algorithm:

• For each key, check if there exists a mirror key in the dataset with the corresponding negative value along the relevant axis.
• When other axes' values match, ensure that the keys are truly mirror images, not just coincidentally similar.

Example in Python:

keys = [(1, 2), (-1, 2), (3, 4), (-3, 4), (5, 6)]

key_set = set(keys)

for x, y in keys:
    mirror = (-x, y)
    if mirror in key_set:
        print(f"Mirror pair found: ({x}, {y}) and {mirror}")

Thus, the check reduces to finding pairs of keys where one coordinate changes sign, and the others match. This allows for correct handling of negative and matching values for mirror points.