df673cad4e
* solvers -> solver * adaptive_functions -> adaptive_function * callbacks -> callback * operators -> operator * pinns -> physics_informed_solver * layers -> block
37 lines
1.2 KiB
Python
37 lines
1.2 KiB
Python
import torch
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from .condition_interface import ConditionInterface
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from ..label_tensor import LabelTensor
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from ..graph import Graph
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from ..utils import check_consistency
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from ..equation.equation_interface import EquationInterface
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class InputPointsEquationCondition(ConditionInterface):
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"""
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Condition for input_points/equation data. This condition must be used every
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time a Physics Informed Loss is needed in the Solver.
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"""
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__slots__ = ["input_points", "equation"]
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def __init__(self, input_points, equation):
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"""
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TODO : add docstring
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"""
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super().__init__()
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self.input_points = input_points
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self.equation = equation
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def __setattr__(self, key, value):
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if key == 'input_points':
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check_consistency(
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value, (LabelTensor)
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) # for now only labeltensors, we need labels for the operator!
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InputPointsEquationCondition.__dict__[key].__set__(self, value)
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elif key == 'equation':
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check_consistency(value, (EquationInterface))
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InputPointsEquationCondition.__dict__[key].__set__(self, value)
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elif key in ('_problem', '_condition_type'):
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super().__setattr__(key, value)
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