47 lines
2.1 KiB
Python
47 lines
2.1 KiB
Python
# import torch
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# from pina.problem import Problem
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# from pina.segment import Segment
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# from pina.cube import Cube
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# from pina.problem2d import Problem2D
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# xmin, xmax, ymin, ymax = -1, 1, -1, 1
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# class EllipticOptimalControl(Problem2D):
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# def __init__(self, alpha=1):
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# def term1(input_, output_):
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# grad_p = self.grad(output_.extract(['p']), input_)
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# gradgrad_p_x1 = self.grad(grad_p.extract(['x1']), input_)
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# gradgrad_p_x2 = self.grad(grad_p.extract(['x2']), input_)
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# yd = 2.0
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# return output_.extract(['y']) - yd - (gradgrad_p_x1.extract(['x1']) + gradgrad_p_x2.extract(['x2']))
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# def term2(input_, output_):
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# grad_y = self.grad(output_.extract(['y']), input_)
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# gradgrad_y_x1 = self.grad(grad_y.extract(['x1']), input_)
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# gradgrad_y_x2 = self.grad(grad_y.extract(['x2']), input_)
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# return - (gradgrad_y_x1.extract(['x1']) + gradgrad_y_x2.extract(['x2'])) - output_.extract(['u'])
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# def term3(input_, output_):
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# return output_.extract(['p']) - output_.extract(['u'])*alpha
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# def nil_dirichlet(input_, output_):
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# y_value = 0.0
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# p_value = 0.0
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# return torch.abs(output_.extract(['y']) - y_value) + torch.abs(output_.extract(['p']) - p_value)
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# self.conditions = {
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# 'gamma1': {'location': Segment((xmin, ymin), (xmax, ymin)), 'func': nil_dirichlet},
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# 'gamma2': {'location': Segment((xmax, ymin), (xmax, ymax)), 'func': nil_dirichlet},
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# 'gamma3': {'location': Segment((xmax, ymax), (xmin, ymax)), 'func': nil_dirichlet},
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# 'gamma4': {'location': Segment((xmin, ymax), (xmin, ymin)), 'func': nil_dirichlet},
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# 'D1': {'location': Cube([[xmin, xmax], [ymin, ymax]]), 'func': [term1, term2, term3]},
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# }
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# self.input_variables = ['x1', 'x2']
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# self.output_variables = ['u', 'p', 'y']
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# self.spatial_domain = Cube([[xmin, xmax], [xmin, xmax]])
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raise NotImplementedError('not available problem at the moment...') |