import numpy as np from scipy.interpolate import interp1d class Solution(np.ndarray): """Brief description of 'Solution'""" pass class SolutionContainer(dict): """Brief description of 'SolutionContainer'""" pass class SteadyStateSolution(np.ndarray): r"""Brief description of 'SteadyStateSolution'""" def __new__(cls, x): obj = np.asarray(x).view(cls) return obj class UnsteadySolution(Solution): """Brief description of 'UnsteadySolution'""" def __new__(cls, x, y): obj = np.asarray(y).view(cls) obj._x = np.asarray(x).view(cls) return obj def _create_interpolant(self): self._interpolant = interp1d(self._x, self, bounds_error=True) def interpolate(self, x): """ Interpolates solution at point 'x'. Parameters ---------- x : float Point at which the solution is to be interpolated Returns ------- ndarray Solution interpolated at the given point 'x' """ # Cache interpolant to avoid overhead if not hasattr(self, "_interpolant"): self._create_interpolant() return self._interpolant(x) __call__ = interpolate class TransientSolution(UnsteadySolution): def interpolate(self, t): """ Interpolates solution at time 't'. Parameters ---------- t : float Time at which the solution is to be interpolated Returns ------- ndarray Transient solution interpolated at the given time 't' Notes ----- 't' must reside inside the 'tspan' used during integration. """ return super().interpolate(x=t) @property def t(self): r""" Wrapper to access the generic _x attribute on the super class """ return self._x class PressureScan(UnsteadySolution): def interpolate(self, p): s = super().interpolate(x=p).astype(self.dtype) return s @property def p(self): r""" Wrapper to access the generic _x attribute on the super class """ return self._x __call__ = interpolate