87 lines
2.5 KiB
Python
87 lines
2.5 KiB
Python
from pydantic import BaseModel, ValidationError
|
|
from typing import List
|
|
import random
|
|
|
|
|
|
class ModelOutput(BaseModel):
|
|
|
|
@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)
|
|
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)
|
|
|
|
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())
|
|
|
|
|
|
class InformationValueModelOutput(ModelOutput):
|
|
given_new: float
|
|
ideal_real: float
|
|
central_marginal: float
|
|
|
|
|
|
class FramingModelOutput(ModelOutput):
|
|
frame_lines: float
|
|
empty_space: float
|
|
colour_contrast: float
|
|
form_contrast: float
|
|
|
|
|
|
class SalienceModelOutput(ModelOutput):
|
|
size: float
|
|
colour: float
|
|
tone: float
|
|
form: float
|
|
positioning: float
|
|
|
|
|
|
if __name__ == '__main__':
|
|
m = InformationValueModelOutput.from_random()
|
|
print(repr(m))
|
|
print(m.highest_score_field())
|
|
print(m.highest_score_value())
|
|
m = FramingModelOutput.from_random()
|
|
print(repr(m))
|
|
print(m.highest_score_field())
|
|
print(m.highest_score_value())
|
|
m = SalienceModelOutput.from_random()
|
|
print(repr(m))
|
|
print(m.highest_score_field())
|
|
print(m.highest_score_value()) |