Source code for mpt4py.functions.function_base

import numpy as np
from typing import Callable, Optional
from mpt4py.base import Vector



class FunctionBase:
	"""
	Abstract base class for scalar-valued functions.
	"""
	def __init__(self, lambda_expr: Optional[Callable[[Vector], float]] = None):
		self._lambda_expr = lambda_expr  # Placeholder for symbolic expression, if needed

	def __call__(self, x: Vector) -> float:
		"""
		Make the function callable.
		"""
		return self._lambda_expr(x)



	def evaluate(self, x: Vector) -> float:
		"""
		Evaluate the function at a given point x.
		"""
		return self._lambda_expr(x)




	def gradient(self, x: Vector) -> Vector:
		"""
		Compute the gradient of the function at a given point x.
		"""
		# TODO: consider using automatic differentiation libraries
		raise NotImplementedError


	@property
	def get_lambda(self) -> Callable[[Vector], float]:
		"""
		Get the symbolic expression of the function, if available.

		Returns:
		sympy expression or None: The symbolic expression of the function.
		"""
		return self._lambda_expr