Additional fix in condition

Author: FilippoOlivo

pina/condition/condition.py

@@ -98,11 +98,11 @@ def __new__(cls, *args, **kwargs):
         - `input`: :class:`~pina.condition.data_condition.DataCondition`
         - `input` and `conditional_variables`:
             :class:`~pina.condition.data_condition.DataCondition`
-
-        :raises ValueError: No valid condition has been found.
         :return: A new condition instance belonging to the proper class.
         :rtype: InputTargetCondition | DomainEquationCondition |
                 InputEquationCondition | DataCondition
+
+        :raises ValueError: No valid condition has been found.
         """
         if len(args) != 0:
             raise ValueError(

pina/condition/data_condition.py

@@ -11,9 +11,8 @@
 
 class DataCondition(ConditionInterface):
     """
-    This condition must be used every time a Unsupervised Loss is needed in
-    the Solver. The `conditional_variable` can be passed as extra-input when
-    the model learns a conditional distribution.
+    Condition defined by input data and conditional variables. It can be used
+    in unsupervised learning problems.
     """
 
     __slots__ = ["input", "conditional_variables"]
@@ -22,24 +21,23 @@ class DataCondition(ConditionInterface):
 
     def __new__(cls, input, conditional_variables=None):
         """
-        Instantiate the appropriate subclass of DataCondition based on the
-        types of input data.
+        Instantiate the appropriate subclass of :class:`DataCondition` based on
+        the type of `input`.
 
         :param input: Input data for the condition.
         :type input: torch.Tensor | LabelTensor | Graph |
             Data | list[Graph] | list[Data] | tuple[Graph] | tuple[Data]
         :param conditional_variables: Conditional variables for the condition.
-        :type conditional_variables: torch.Tensor | LabelTensor
+        :type conditional_variables: torch.Tensor | LabelTensor, optional
         :return: Subclass of DataCondition.
         :rtype: pina.condition.data_condition.TensorDataCondition |
             pina.condition.data_condition.GraphDataCondition
 
         :raises ValueError: If input is not of type :class:`torch.Tensor`,
             :class:`~pina.label_tensor.LabelTensor`, :class:`~pina.graph.Graph`,
             or :class:`~torch_geometric.data.Data`.
-
-
         """
+
         if cls != DataCondition:
             return super().__new__(cls)
         if isinstance(input, (torch.Tensor, LabelTensor)):
@@ -69,8 +67,8 @@ def __init__(self, input, conditional_variables=None):
 
         .. note::
             If either `input` is composed by a list of
-            :class:`~pina.graph.Graph` or :class:`~torch_geometric.data.Data`
-            objects, all elements must have the same structure (keys and data
+            :class:`~pina.graph.Graph` or :class:`~torch_geometric.data.Data`,
+            all elements must have the same structure (keys and data
             types)
         """
 

pina/condition/domain_equation_condition.py

@@ -10,15 +10,16 @@
 
 class DomainEquationCondition(ConditionInterface):
     """
-    Condition for domain/equation data. This condition must be used every
-    time a Physics Informed Loss is needed in the Solver.
+    Condition defined by a domain and an equation. It can be used in Physics
+    Informed problems. Before using this condition, make sure that input data
+    are correctly sampled from the domain.
     """
 
     __slots__ = ["domain", "equation"]
 
     def __init__(self, domain, equation):
         """
-        Initialize the object by storing the domain and equation.
+        Initialise the object by storing the domain and equation.
 
         :param DomainInterface domain: Domain object containing the domain data.
         :param EquationInterface equation: Equation object containing the

pina/condition/input_equation_condition.py

@@ -12,8 +12,8 @@
 
 class InputEquationCondition(ConditionInterface):
     """
-    Condition for input/equation data. This condition must be used every
-    time a Physics Informed Loss is needed in the Solver.
+    Condition defined by input data and an equation. This condition can be
+    used in a Physics Informed problems.
     """
 
     __slots__ = ["input", "equation"]
@@ -22,10 +22,10 @@ class InputEquationCondition(ConditionInterface):
 
     def __new__(cls, input, equation):
         """
-        Instantiate the appropriate subclass of InputEquationCondition based on
-        the type of input data.
+        Instantiate the appropriate subclass of :class:`InputEquationCondition`
+        based on the type of `input`.
 
-        :param input: Input data. It can be a LabelTensor or a Graph object.
+        :param input: Input data for the condition.
         :type input: LabelTensor | Graph |  list[Graph] | tuple[Graph]
         :param EquationInterface equation: Equation object containing the
             equation function.

pina/condition/input_target_condition.py

@@ -11,8 +11,8 @@
 
 class InputTargetCondition(ConditionInterface):
     """
-    Condition for domain/equation data. This condition must be used every
-    time a Physics Informed or a Supervised Loss is needed in the Solver.
+    Condition defined by input and target data. This condition can be used in
+    both supervised learning and Physics-informed problems.
     """
 
     __slots__ = ["input", "target"]
@@ -25,15 +25,11 @@ def __new__(cls, input, target):
         the types of input and target data.
 
         :param input: Input data for the condition.
-        :type input: torch.Tensor | LabelTensor | Graph |
-            torch_geometric.data.Data | list[Graph] |
-            list[torch_geometric.data.Data] | tuple[Graph] |
-            tuple[torch_geometric.data.Data]
+        :type input: torch.Tensor | LabelTensor | Graph | Data | list[Graph] |
+            list[Data] | tuple[Graph] | tuple[Data]
         :param target: Target data for the condition.
-        :type target: torch.Tensor | LabelTensor | Graph |
-            torch_geometric.data.Data | list[Graph] |
-            list[torch_geometric.data.Data] | tuple[Graph] |
-            tuple[torch_geometric.data.Data]
+        :type target: torch.Tensor | LabelTensor | Graph | Data | list[Graph] |
+            list[Data] | tuple[Graph] | tuple[Data]
         :return: Subclass of InputTargetCondition
         :rtype: pina.condition.input_target_condition.
             TensorInputTensorTargetCondition |
@@ -43,7 +39,7 @@ def __new__(cls, input, target):
             GraphInputTensorTargetCondition |
             pina.condition.input_target_condition.GraphInputGraphTargetCondition
 
-        :raises ValueError: If input and or target are not of type
+        :raises ValueError: If `input` and/or `target` are not of type
             :class:`torch.Tensor`, :class:`~pina.label_tensor.LabelTensor`,
             :class:`~pina.graph.Graph`, or :class:`~torch_geometric.data.Data`.
         """
@@ -85,12 +81,11 @@ def __new__(cls, input, target):
 
     def __init__(self, input, target):
         """
-        Initialize the object storing the input and target data.
+        Initialize the object by storing the `input` and `target` data.
 
         :param input: Input data for the condition.
         :type input: torch.Tensor | LabelTensor | Graph | Data | list[Graph] |
-            list[Data] | tuple[Graph] |
-            tuple[Data]
+            list[Data] | tuple[Graph] | tuple[Data]
         :param target: Target data for the condition.
         :type target: torch.Tensor | LabelTensor | Graph | Data | list[Graph] |
             list[Data] | tuple[Graph] | tuple[Data]
@@ -122,29 +117,29 @@ def _check_input_target_len(input, target):
 class TensorInputTensorTargetCondition(InputTargetCondition):
     """
     InputTargetCondition subclass for :class:`torch.Tensor` or
-    :class:`~pina.label_tensor.LabelTensor` input and target data.
+    :class:`~pina.label_tensor.LabelTensor` `input` and `target` data.
     """
 
 
 class TensorInputGraphTargetCondition(InputTargetCondition):
     """
     InputTargetCondition subclass for :class:`torch.Tensor` or
-    :class:`~pina.label_tensor.LabelTensor` input and
-    :class:`~pina.graph.Graph` or :class:`~torch_geometric.data.Data` target
+    :class:`~pina.label_tensor.LabelTensor` `input` and
+    :class:`~pina.graph.Graph` or :class:`~torch_geometric.data.Data` `target`
     data.
     """
 
 
 class GraphInputTensorTargetCondition(InputTargetCondition):
     """
     InputTargetCondition subclass for :class:`~pina.graph.Graph` o
-    :class:`~torch_geometric.data.Data` input and :class:`torch.Tensor` or
-    :class:`~pina.label_tensor.LabelTensor` target data.
+    :class:`~torch_geometric.data.Data` `input` and :class:`torch.Tensor` or
+    :class:`~pina.label_tensor.LabelTensor` `target` data.
     """
 
 
 class GraphInputGraphTargetCondition(InputTargetCondition):
     """
     InputTargetCondition subclass for :class:`~pina.graph.Graph`/
-    :class:`~torch_geometric.data.Data` input and target data.
+    :class:`~torch_geometric.data.Data` `input` and `target` data.
     """