Improve conditions and refactor dataset classes (#475)

* Reimplement conditions

* Refactor datasets and implement LabelBatch

---------

Co-authored-by: Dario Coscia <dariocos99@gmail.com>

pina/problem/zoo/inverse_diffusion_reaction.py

@@ -46,8 +46,8 @@ class InverseDiffusionReactionProblem(
             equation=Equation(diffusion_reaction),
         ),
         "data": Condition(
-            input_points=LabelTensor(torch.randn(10, 2), ["x", "t"]),
-            output_points=LabelTensor(torch.randn(10, 1), ["u"]),
+            input=LabelTensor(torch.randn(10, 2), ["x", "t"]),
+            target=LabelTensor(torch.randn(10, 1), ["u"]),
         ),
     }
 

pina/problem/zoo/inverse_poisson_2d_square.py

@@ -50,7 +50,7 @@ class InversePoisson2DSquareProblem(SpatialProblem, InverseProblem):
         "nil_g4": Condition(domain="g4", equation=FixedValue(0.0)),
         "laplace_D": Condition(domain="D", equation=Equation(laplace_equation)),
         "data": Condition(
-            input_points=data_input.extract(["x", "y"]),
-            output_points=data_output,
+            input=data_input.extract(["x", "y"]),
+            target=data_output,
         ),
     }

pina/problem/zoo/supervised_problem.py

@@ -8,7 +8,7 @@ class SupervisedProblem(AbstractProblem):
     A problem definition for supervised learning in PINA.
 
     This class allows an easy and straightforward definition of a Supervised problem,
-    based on a single condition of type `InputOutputPointsCondition`
+    based on a single condition of type `InputTargetCondition`
 
     :Example:
         >>> import torch
@@ -31,7 +31,5 @@ class SupervisedProblem(AbstractProblem):
         """
         if isinstance(input_, Graph):
             input_ = input_.data
-        self.conditions["data"] = Condition(
-            input_points=input_, output_points=output_
-        )
+        self.conditions["data"] = Condition(input=input_, target=output_)
         super().__init__()