"""Definition of DataModel base class."""

import random

from pydantic import BaseModel, ValidationError
from torch import Tensor


class DataModel(BaseModel):
    """DataModel base class."""

    @classmethod
    def classname(cls) -> str:
        """Return classname."""
        return cls.__name__

    @classmethod
    def list_fields(cls) -> list[str]:
        """List options that are stored as attributes."""
        return list(cls.model_fields.keys())

    @classmethod
    def from_random(cls):
        """Instantiate with random numbers."""
        kwargs = {field: random.random() for field in cls.list_fields()}
        return cls(**kwargs)

    @classmethod
    def from_choice(cls, option: str):
        """Instantiate from choice."""
        if option is None:
            raise ValidationError()
        assert isinstance(option, str), 'option is not a string'
        allowed_options_list = cls.list_fields()
        assert (
            option in allowed_options_list
        ), f"{option} is not among allowed fields {allowed_options_list}"
        kwargs = {field: 0 for field in cls.list_fields()}
        kwargs[option] = 1
        return cls(**kwargs)

    @classmethod
    def from_tensor(cls, tensor: Tensor):
        """Instantiate from list of values."""
        assert tensor.size(dim=0) == 1, f'tensor batch larger than 1: {tensor}'
        data_list = [float(t.item()) for t in tensor[0]]
        kwargs = dict(zip(cls.list_fields(), data_list))
        return cls(**kwargs)

    def __repr__(self) -> str:
        model_dict = self.model_dump()
        model_repr_str = f'{self.classname()}('
        model_repr_str += ', '.join(
            [f'{field}={value:.3f}' for field, value in model_dict.items()],
        )
        model_repr_str += ')'
        return model_repr_str

    def highest_score_field(self) -> str:
        """Return name of field with highest score."""
        model_dict = self.model_dump()
        return max(model_dict, key=lambda k: model_dict[k])

    def highest_score_value(self) -> float:
        """Return value of field with highest score."""
        model_dict = self.model_dump()
        return max(model_dict.values())