from pydantic import BaseModel
from src.utils import list_to_matrix, secure_fisher_yates_shuffle, matrix_to_list


class UserInterface(BaseModel):
    interface_index: list[int]
    numb_sets: int
    numb_keys: int

    @classmethod
    def new_interface(cls, numb_sets: int, numb_keys: int):
        return UserInterface(
            interface_index=secure_fisher_yates_shuffle(list(range(numb_sets*numb_keys))),
            numb_sets=numb_sets,
            numb_keys=numb_keys,
        )

    def disperse_interface(self):
        user_interface_matrix = list_to_matrix(self.interface_index, self.numb_sets)
        shuffled_keys = secure_fisher_yates_shuffle(user_interface_matrix)
        dispersed_interface = self._random_attribute_rotation(shuffled_keys)
        self.interface_index = matrix_to_list(dispersed_interface)

    @staticmethod
    def matrix_transpose(interface: list[list[int]]) -> list[list[int]]:
        return [list(row) for row in zip(*interface)]

    def shuffle_interface(self):
        pass

    def _random_attribute_rotation(self, user_interface: list[list[int]]) -> list[list[int]]:
        attr_rotation = secure_fisher_yates_shuffle(list(range(self.numb_keys)))[:self.numb_sets]
        transposed_user_interface = self.matrix_transpose(user_interface)
        assert (len(attr_rotation) == len(transposed_user_interface))
        for idx, attr_set in enumerate(transposed_user_interface):
            rotation = attr_rotation[idx]
            transposed_user_interface[idx] = attr_set[rotation:] + attr_set[:rotation]
        return self.matrix_transpose(transposed_user_interface)

    def attribute_adjacency_graph(self) -> dict[int, set[int]]:
        user_interface_keypad = list_to_matrix(self.interface_index, self.numb_sets)
        graph = {}
        for key in user_interface_keypad:
            for attr in key:
                graph[attr] = set(key)
                graph[attr].remove(attr)

        return graph