Renaming

* solvers -> solver
* adaptive_functions -> adaptive_function
* callbacks -> callback
* operators -> operator
* pinns -> physics_informed_solver
* layers -> block

Author: dario-coscia

pina/__init__.py

@@ -10,6 +10,7 @@
 
 from .label_tensor import LabelTensor
 from .graph import Graph
-from .solvers.solver import SolverInterface, MultiSolverInterface
+from .solver import SolverInterface, MultiSolverInterface
 from .trainer import Trainer
 from .condition.condition import Condition
+from .data import PinaDataModule

pina/adaptive_functions/__init__.py pina/adaptive_function/__init__.pypina/adaptive_functions/__init__.py renamed to pina/adaptive_function/__init__.py

@@ -9,7 +9,7 @@
 class AdaptiveActivationFunctionInterface(torch.nn.Module, metaclass=ABCMeta):
     r"""
     The
-    :class:`~pina.adaptive_functions.adaptive_func_interface.AdaptiveActivationFunctionInterface`
+    :class:`~pina.adaptive_function.adaptive_func_interface.AdaptiveActivationFunctionInterface`
     class makes a :class:`torch.nn.Module` activation function into an adaptive
     trainable activation function. If one wants to create an adpative activation
     function, this class must be use as base class.

pina/adaptive_functions/adaptive_func.py pina/adaptive_function/adaptive_func.pypina/adaptive_functions/adaptive_func.py renamed to pina/adaptive_function/adaptive_func.py

@@ -0,0 +1,10 @@
+__all__ = [
+    "SwitchOptimizer",
+    "R3Refinement",
+    "MetricTracker",
+    "PINAProgressBar",
+]
+
+from .optimizer_callback import SwitchOptimizer
+from .adaptive_refinment_callback import R3Refinement
+from .processing_callback import MetricTracker, PINAProgressBar

…ive_functions/adaptive_func_interface.py …tive_function/adaptive_func_interface.pypina/adaptive_functions/adaptive_func_interface.py renamed to pina/adaptive_function/adaptive_func_interface.py pina/adaptive_functions/adaptive_func_interface.py renamed to pina/adaptive_function/adaptive_func_interface.py

@@ -19,7 +19,7 @@ def __init__(self, new_optimizers, epoch_switch):
 
         :param new_optimizers: The model optimizers to switch to. Can be a
             single :class:`torch.optim.Optimizer` or a list of them for multiple
-            model solvers.
+            model solver.
         :type new_optimizers: pina.optim.TorchOptimizer | list
         :param epoch_switch: The epoch at which to switch to the new optimizer.
         :type epoch_switch: int

pina/callback/__init__.py

@@ -87,12 +87,12 @@ def __init__(self, metrics="val", **kwargs):
         :Keyword Arguments:
             The additional keyword arguments specify the progress bar
             and can be choosen from the `pytorch-lightning
-            TQDMProgressBar API <https://lightning.ai/docs/pytorch/stable/_modules/lightning/pytorch/callbacks/progress/tqdm_progress.html#TQDMProgressBar>`_
+            TQDMProgressBar API <https://lightning.ai/docs/pytorch/stable/_modules/lightning/pytorch/callback/progress/tqdm_progress.html#TQDMProgressBar>`_
 
         Example:
             >>> pbar = PINAProgressBar(['mean'])
             >>> # ... Perform training ...
-            >>> trainer = Trainer(solver, callbacks=[pbar])
+            >>> trainer = Trainer(solver, callback=[pbar])
         """
         super().__init__(**kwargs)
         # check consistency

…allbacks/adaptive_refinment_callbacks.py …/callback/adaptive_refinment_callback.pypina/callbacks/adaptive_refinment_callbacks.py renamed to pina/callback/adaptive_refinment_callback.py pina/callbacks/adaptive_refinment_callbacks.py renamed to pina/callback/adaptive_refinment_callback.py

@@ -27,7 +27,7 @@ def __setattr__(self, key, value):
         if key == 'input_points':
             check_consistency(
                 value, (LabelTensor)
-            )  # for now only labeltensors, we need labels for the operators!
+            )  # for now only labeltensors, we need labels for the operator!
             InputPointsEquationCondition.__dict__[key].__set__(self, value)
         elif key == 'equation':
             check_consistency(value, (EquationInterface))