fix examples (#21)

examples/problems/burgers.py

@@ -8,10 +8,9 @@ from pina.span import Span
 
 class Burgers1D(TimeDependentProblem, SpatialProblem):
 
-    spatial_variables = ['x']
-    temporal_variable = ['t']
     output_variables = ['u']
-    domain = Span({'x': [-1, 1], 't': [0, 1]})
+    spatial_domain = Span({'x': [-1, 1]})
+    temporal_domain = Span({'t': [0, 1]})
 
     def burger_equation(input_, output_):
         du = grad(output_, input_)

examples/problems/parametric_elliptic_optimal_control_alpha_variable.py

@@ -16,11 +16,9 @@ class ParametricEllipticOptimalControl(SpatialProblem, ParametricProblem):
     x_range = [xmin, xmax]
     y_range = [ymin, ymax]
 
-    spatial_variables = ['x1', 'x2']
-    parameters = ['mu', 'alpha']
     output_variables = ['u', 'p', 'y']
-    domain = Span({
-        'x1': x_range, 'x2': y_range, 'mu': mu_range, 'alpha': a_range})
+    spatial_domain = Span({'x1': x_range, 'x2': y_range})
+    parameter_domain = Span({'mu': mu_range, 'alpha': a_range})
 
 
     def term1(input_, output_):

examples/problems/parametric_poisson.py

@@ -7,10 +7,9 @@ from pina import Span, Condition
 
 class ParametricPoisson(SpatialProblem, ParametricProblem):
 
-    spatial_variables = ['x', 'y']
-    parameters = ['mu1', 'mu2']
     output_variables = ['u']
-    domain = Span({'x': [-1, 1], 'y': [-1, 1]})
+    spatial_domain = Span({'x': [-1, 1], 'y': [-1, 1]})
+    parameter_domain = Span({'mu1': [-1, 1], 'mu2': [-1, 1]})
 
     def laplace_equation(input_, output_):
         force_term = torch.exp(

examples/problems/poisson.py

@@ -8,9 +8,8 @@ from pina import Condition, Span
 
 class Poisson(SpatialProblem):
 
-    spatial_variables = ['x', 'y']
     output_variables = ['u']
-    domain = Span({'x': [0, 1], 'y': [0, 1]})
+    spatial_domain = Span({'x': [0, 1], 'y': [0, 1]})
 
     def laplace_equation(input_, output_):
         force_term = (torch.sin(input_.extract(['x'])*torch.pi) *
@@ -30,7 +29,11 @@ class Poisson(SpatialProblem):
         'D': Condition(Span({'x': [0, 1], 'y': [0, 1]}), laplace_equation),
     }
 
-    def poisson_sol(self, x, y):
-        return -(np.sin(x*np.pi)*np.sin(y*np.pi))/(2*np.pi**2)
+    def poisson_sol(self, pts):
+        return -(
+            torch.sin(pts.extract(['x'])*torch.pi)*
+            torch.sin(pts.extract(['y'])*torch.pi)
+        )/(2*torch.pi**2)
+        #return -(np.sin(x*np.pi)*np.sin(y*np.pi))/(2*np.pi**2)
 
     truth_solution = poisson_sol

examples/problems/stokes.py

@@ -8,9 +8,8 @@ from pina import Condition, Span, LabelTensor
 
 class Stokes(SpatialProblem):
 
-    spatial_variables = ['x', 'y']
     output_variables = ['ux', 'uy', 'p']
-    domain = Span({'x': [-2, 2], 'y': [-1, 1]})
+    spatial_domain = Span({'x': [-2, 2], 'y': [-1, 1]})
 
     def momentum(input_, output_):
         nabla_ = torch.hstack((LabelTensor(nabla(output_.extract(['ux']), input_), ['x']),