OpenPNM / data /src /openpnm /algorithms /_solution.py
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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