import numpy as np import torch from pina.segment import Segment from pina.cube import Cube from pina.problem2d import Problem2D xmin, xmax, ymin, ymax = -1, 1, -1, 1 class ParametricEllipticOptimalControl(Problem2D): def __init__(self, alpha=1): def term1(input_, param_, output_): grad_p = self.grad(output_['p'], input_) gradgrad_p_x1 = self.grad(grad_p['x1'], input_) gradgrad_p_x2 = self.grad(grad_p['x2'], input_) return output_['y'] - param_ - (gradgrad_p_x1['x1'] + gradgrad_p_x2['x2']) def term2(input_, param_, output_): grad_y = self.grad(output_['y'], input_) gradgrad_y_x1 = self.grad(grad_y['x1'], input_) gradgrad_y_x2 = self.grad(grad_y['x2'], input_) return - (gradgrad_y_x1['x1'] + gradgrad_y_x2['x2']) - output_['u_param'] def term3(input_, param_, output_): return output_['p'] - output_['u_param']*alpha def term(input_, param_, output_): return term1( input_, param_, output_) +term2( input_, param_, output_) + term3( input_, param_, output_) def nil_dirichlet(input_, param_, output_): y_value = 0.0 p_value = 0.0 return torch.abs(output_['y'] - y_value) + torch.abs(output_['p'] - p_value) self.conditions = { 'gamma1': {'location': Segment((xmin, ymin), (xmax, ymin)), 'func': nil_dirichlet}, 'gamma2': {'location': Segment((xmax, ymin), (xmax, ymax)), 'func': nil_dirichlet}, 'gamma3': {'location': Segment((xmax, ymax), (xmin, ymax)), 'func': nil_dirichlet}, 'gamma4': {'location': Segment((xmin, ymax), (xmin, ymin)), 'func': nil_dirichlet}, 'D1': {'location': Cube([[xmin, xmax], [ymin, ymax]]), 'func': term}, #'D2': {'location': Cube([[0, 1], [0, 1]]), 'func': term2}, #'D3': {'location': Cube([[0, 1], [0, 1]]), 'func': term3} } self.input_variables = ['x1', 'x2'] self.output_variables = ['u', 'p', 'y'] self.parameters = ['mu'] self.spatial_domain = Cube([[xmin, xmax], [xmin, xmax]]) self.parameter_domain = np.array([[0.5, 3]])