Refactoring code

examples/problems/parametric_elliptic_optimal_control.py

@@ -0,0 +1,53 @@
+import numpy as np
+import torch
+from pina.problem import Problem
+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]])
+