equation class, fix minor bugs, diff domain (#89)

* equation class
* difference domain
* dummy dataloader
* writer class
* refactoring and minor fix

pina/condition.py

@@ -1,6 +1,7 @@
 """ Condition module. """
 from .label_tensor import LabelTensor
-from .location import Location
+from .geometry import Location
+from .equation.equation import Equation
 
 def dummy(a):
     """Dummy function for testing purposes."""
@@ -17,13 +18,13 @@ class Condition:
         case, the model is trained to produce the output points given the input
         points.
 
-        2. By specifying the location and the function of the condition; in such
-        a case, the model is trained to minimize that function by evaluating it
-        at some samples of the location.
+        2. By specifying the location and the equation of the condition; in such
+        a case, the model is trained to minimize the equation residual by
+        evaluating it at some samples of the location.
 
-        3. By specifying the input points and the function of the condition; in
-        such a case, the model is trained to minimize that function by
-        evaluating it at the input points.
+        3. By specifying the input points and the equation of the condition; in
+        such a case, the model is trained to minimize the equation residual by
+        evaluating it at the passed input points.
 
     Example::
 
@@ -40,15 +41,15 @@ class Condition:
     >>>     output_points=example_output_pts)
     >>> Condition(
     >>>     location=example_domain,
-    >>>     function=example_dirichlet)
+    >>>     equation=example_dirichlet)
     >>> Condition(
     >>>     input_points=example_input_pts,
-    >>>     function=example_dirichlet)
+    >>>     equation=example_dirichlet)
 
     """
 
     __slots__ = [
-        'input_points', 'output_points', 'location', 'function',
+        'input_points', 'output_points', 'location', 'equation',
         'data_weight'
     ]
 
@@ -70,8 +71,8 @@ class Condition:
 
         if (
             sorted(kwargs.keys()) != sorted(['input_points', 'output_points']) and
-            sorted(kwargs.keys()) != sorted(['location', 'function']) and
-            sorted(kwargs.keys()) != sorted(['input_points', 'function'])
+            sorted(kwargs.keys()) != sorted(['location', 'equation']) and
+            sorted(kwargs.keys()) != sorted(['input_points', 'equation'])
         ):
             raise ValueError(f'Invalid keyword arguments {kwargs.keys()}.')
 
@@ -81,16 +82,8 @@ class Condition:
             raise TypeError('`output_points` must be a torch.Tensor.')
         if not self._dictvalue_isinstance(kwargs, 'location', Location):
             raise TypeError('`location` must be a Location.')
-
-        if 'function' in kwargs:
-            if not isinstance(kwargs['function'], list):                        
-                kwargs['function'] = [kwargs['function']]
-
-
-            for i, func in enumerate(kwargs['function']):
-                if not callable(func):
-                    raise TypeError(
-                        f'`function[{i}]` must be a callable function.')
+        if not self._dictvalue_isinstance(kwargs, 'equation', Equation):
+            raise TypeError('`equation` must be a Equation.')
 
         for key, value in kwargs.items():
             setattr(self, key, value)