Fix Codacy Warnings (#477)

---------

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

pina/problem/zoo/__init__.py

@@ -1,3 +1,5 @@
+"""TODO"""
+
 __all__ = [
     "Poisson2DSquareProblem",
     "SupervisedProblem",

pina/problem/zoo/poisson_2d_square.py

@@ -1,12 +1,12 @@
 """Definition of the Poisson problem on a square domain."""
 
-from pina.problem import SpatialProblem
-from pina.operator import laplacian
-from pina import Condition
-from pina.domain import CartesianDomain
-from pina.equation.equation import Equation
-from pina.equation.equation_factory import FixedValue
 import torch
+from ..spatial_problem import SpatialProblem
+from ...operator import laplacian
+from ... import Condition
+from ...domain import CartesianDomain
+from ...equation.equation import Equation
+from ...equation.equation_factory import FixedValue
 
 
 def laplace_equation(input_, output_):
@@ -48,6 +48,8 @@ class Poisson2DSquareProblem(SpatialProblem):
     }
 
     def poisson_sol(self, pts):
+        """TODO"""
+
         return -(
             torch.sin(pts.extract(["x"]) * torch.pi)
             * torch.sin(pts.extract(["y"]) * torch.pi)

pina/problem/zoo/supervised_problem.py

@@ -1,14 +1,17 @@
-from pina.problem import AbstractProblem
-from pina import Condition
-from pina import Graph
+"""TODO"""
+
+from ..abstract_problem import AbstractProblem
+from ... import Condition
+from ... import Graph
 
 
 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 `InputTargetCondition`
+    This class allows an easy and straightforward definition of a
+    Supervised problem, based on a single condition of type
+    `InputTargetCondition`
 
     :Example:
         >>> import torch
@@ -17,7 +20,7 @@ class SupervisedProblem(AbstractProblem):
         >>> problem = SupervisedProblem(input_data, output_data)
     """
 
-    conditions = dict()
+    conditions = {}
     output_variables = None
 
     def __init__(self, input_, output_):