Interface + base class structure for data module

docs/source/_rst/_code.rst

@@ -18,14 +18,17 @@ The pipeline to solve differential equations with PINA follows just five steps:
     5. Train the model with the PINA :doc:`Trainer <solver/solver_interface>`, enhance the train with `Callbacks`_
 
 
-Trainer, Dataset and Datamodule
---------------------------------
+Trainer, Data Loader and Data Module
+----------------------------------------
 .. toctree::
     :titlesonly:
 
     Trainer <trainer.rst>
-    Dataset <data/dataset.rst>
-    DataModule <data/data_module.rst>
+    Data Module <data/data_module.rst>
+    Single-Batch Data Loader <data/single_batch_data_loader.rst>
+    Aggregator <data/aggregator.rst>
+    Creator <data/creator.rst>
+    Condition Subset <data/condition_subset.rst>
 
 Data Types
 ------------

docs/source/_rst/data/aggregator.rst

@@ -0,0 +1,9 @@
+Aggregator
+================
+.. currentmodule:: pina.data.aggregator
+
+.. automodule:: pina._src.data.aggregator
+
+.. autoclass::  pina._src.data.aggregator._Aggregator
+    :members:
+    :show-inheritance:

docs/source/_rst/data/condition_subset.rst

@@ -0,0 +1,9 @@
+Condition Subset
+================
+.. currentmodule:: pina.data.condition_subset
+
+.. automodule:: pina._src.data.condition_subset
+
+.. autoclass::  pina._src.data.condition_subset._ConditionSubset
+    :members:
+    :show-inheritance:

docs/source/_rst/data/creator.rst

@@ -0,0 +1,9 @@
+Creator
+=======
+.. currentmodule:: pina.data.creator
+
+.. automodule:: pina._src.data.creator
+
+.. autoclass::  pina._src.data.creator._Creator
+    :members:
+    :show-inheritance:

docs/source/_rst/data/data_module.rst

@@ -2,6 +2,6 @@ DataModule
 ======================
 .. currentmodule:: pina.data.data_module
 
-.. autoclass:: pina._src.data.data_module.PinaDataModule
+.. autoclass:: pina._src.data.data_module.DataModule
     :members:
     :show-inheritance:

docs/source/_rst/data/single_batch_data_loader.rst

@@ -0,0 +1,9 @@
+Single-Batch Data Loader
+===========================
+.. currentmodule:: pina.data.single_batch_data_loader
+
+.. automodule:: pina._src.data.single_batch_data_loader
+
+.. autoclass::  pina._src.data.single_batch_data_loader._SingleBatchDataLoader
+    :members:
+    :show-inheritance:

pina/__init__.py

@@ -1,6 +1,4 @@
 """
-PINA: Physics-Informed Neural Analysis.
-
 A specialized framework for Scientific Machine Learning (SciML), providing
 tools for Physics-Informed Neural Networks (PINNs), Neural Operators,
 and data-driven physical modeling.
@@ -10,12 +8,30 @@
     "LabelTensor",
     "Trainer",
     "Condition",
-    "PinaDataModule",
+    "DataModule",
     "Graph",
 ]
 
 from pina._src.core.label_tensor import LabelTensor
 from pina._src.core.graph import Graph
 from pina._src.core.trainer import Trainer
 from pina._src.condition.condition import Condition
-from pina._src.data.data_module import PinaDataModule
+from pina._src.data.data_module import DataModule
+
+# Back-compatibility with version 0.2, to be removed soon
+import warnings
+
+_DEPRECATED_IMPORTS = {"PinaDataModule": "DataModule"}
+
+
+def __getattr__(name):
+    if name in _DEPRECATED_IMPORTS:
+
+        warnings.warn(
+            f"Importing '{name}' from 'pina' is deprecated; use "
+            f"pina.{_DEPRECATED_IMPORTS[name]} instead.",
+            DeprecationWarning,
+            stacklevel=2,
+        )
+
+        return globals()[_DEPRECATED_IMPORTS[name]]

pina/_src/callback/refinement/base_refinement.py

@@ -99,7 +99,7 @@ def on_train_start(self, trainer, solver):
         # Initialize dataset and compute initial population size
         self._dataset = trainer.datamodule.train_datasets
         self._initial_population_size = {
-            cond: self.dataset[cond].length
+            cond: self.dataset[cond].dataset_length
             for cond in self._condition_to_update
         }
 

pina/_src/condition/base_condition.py

@@ -8,7 +8,7 @@
 from pina._src.core.graph import LabelBatch
 from pina._src.core.label_tensor import LabelTensor
 from pina._src.core.utils import check_consistency
-from pina._src.data.dummy_dataloader import DummyDataloader
+from pina._src.data.single_batch_data_loader import _SingleBatchDataLoader
 from pina._src.problem.problem_interface import ProblemInterface
 
 
@@ -74,9 +74,9 @@ def create_dataloader(
         :return: The DataLoader for the condition.
         :rtype: torch.utils.data.DataLoader
         """
-        # If batching the entire dataset, return a DummyDataloader
+        # If batching the entire dataset, return a _SingleBatchDataLoader
         if batch_size == len(dataset):
-            return DummyDataloader(dataset)
+            return _SingleBatchDataLoader(dataset)
 
         # Otherwise, return a regular DataLoader with the appropriate collate
         return DataLoader(

pina/_src/condition/time_series_condition.py

@@ -200,7 +200,7 @@ def evaluate(self, batch, solver):
             raise ValueError(
                 "The provided input tensor must have at least 4 dimensions:"
                 " [trajectories, windows, time_steps, *features]."
-                f" Got shape {batch["input"].shape}."
+                f" Got shape {batch['input'].shape}."
             )
 
         # Copy the kwargs to avoid modifying the original settings