Merge pull request #204 from bessagroup/mpvanderschelling/issue194

Fixes #194

src/f3dasm/_src/datageneration/datagenerator.py

@@ -7,6 +7,7 @@
 
 # Standard
 import sys
+from abc import abstractmethod
 from functools import partial
 from typing import Any, Callable
 
@@ -43,30 +44,80 @@ class DataGenerator:
  """Base class for a data generator"""
 
  def pre_process(self, experiment_sample: ExperimentSample, **kwargs) -> None:
- """Function that handles the pre-processing"""
+ """Interface function that handles the pre-processing of the data generator
+
+ Notes
+ -----
+ If not implemented the function will be skipped
+
+ The experiment_sample is cached inside the data generator. This
+ allows the user to access the experiment_sample in the pre_process, execute
+ and post_process functions as a class variable called self.experiment_sample.
+ """
  ...
 
+ @abstractmethod
  def execute(self, **kwargs) -> None:
- """Function that calls the FEM simulator the pre-processing"""
- raise NotImplementedError("No execute function implemented!")
+ """Interface function that handles the execution of the data generator
+
+ Raises
+ ------
+ NotImplementedError
+ If the function is not implemented by the user
+
+ Notes
+ -----
+ The experiment_sample is cached inside the data generator. This
+ allows the user to access the experiment_sample in the pre_process, execute
+ and post_process functions as a class variable called self.experiment_sample.
+ """
+
+ ...
 
  def post_process(self, experiment_sample: ExperimentSample, **kwargs) -> None:
- """Function that handles the post-processing"""
+ """Interface function that handles the post-processing of the data generator
+
+ Notes
+ -----
+ If not implemented the function will be skipped
+
+ The experiment_sample is cached inside the data generator. This
+ allows the user to access the experiment_sample in the pre_process, execute
+ and post_process functions as a class variable called self.experiment_sample.
+ """
  ...
 
  @time_and_log
  def _run(self, experiment_sample: ExperimentSample, **kwargs) -> ExperimentSample:
- """Run the data generator
+ """
+ Run the data generator
+ This function chains the following methods together
+
+ * pre_process(); to combine the experiment_sample and the parameters
+ of the data generator to an input file that can be used to run the data generator
+
+ * execute(); to run the data generator and generate the response of the experiment
+
+ * post_process(); to process the response of the experiment and store it back
+ in the experiment_sample
+
+ The function also caches the experiment_sample in the data generator. This
+ allows the user to access the experiment_sample in the pre_process, execute
+ and post_process functions as a class variable called self.experiment_sample.
 
  Parameters
  ----------
  ExperimentSample : ExperimentSample
  The design to run the data generator on
 
+ kwargs : dict
+ The keyword arguments to pass to the pre_process, execute and post_process
+
  Returns
  -------
  ExperimentSample
- Processed design
+ Processed design with the response of the data generator saved in the
+ experiment_sample
  """
  # Cache the design
  self.experiment_sample: ExperimentSample = experiment_sample
@@ -88,7 +139,25 @@ def _post_simulation(self) -> None:
  ...
 
  def add_pre_process(self, func: Callable, **kwargs):
+ """Add a pre-processing function to the data generator
+
+ Parameters
+ ----------
+ func : Callable
+ The function to add to the pre-processing
+ kwargs : dict
+ The keyword arguments to pass to the pre-processing function
+ """
  self.pre_process = partial(func, **kwargs)
 
  def add_post_process(self, func: Callable, **kwargs):
+ """Add a post-processing function to the data generator
+
+ Parameters
+ ----------
+ func : Callable
+ The function to add to the post-processing
+ kwargs : dict
+ The keyword arguments to pass to the post-processing function
+ """
  self.post_process = partial(func, **kwargs)