Files
visual_critical_discourse_a…/src/model_experiential/classes.py
T
2024-02-19 20:21:18 +01:00

69 lines
2.1 KiB
Python

from pydantic import BaseModel
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)
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 ExperientialModelOutput(ModelOutput):
non_transactional_action: float
non_transactional_reaction: float
unidirectional_transactional_action: float
unidirectional_transactional_reaction: float
bidirectional_transactional_action: float
bidirectional_transactional_reaction: float
conversion: float
speech_process: float
classification_overt_taxonomy: float
analytical_exhaustive: float
analytical_disarranged: float
analytical_temporal: float
analytical_distributed: float
analytical_topological: float
analytical_exploded: float
analytical_inclusive: float
symbolic_suggestive: float
symbolic_attributive: float
if __name__ == '__main__':
m = ExperientialModelOutput.from_random()
print(m)
print(repr(m))
print(m.highest_score_field())
print(m.highest_score_value())