updated datageneration base class

docs/source/rst_doc_files/classes/datageneration/datagenerator.rst

@@ -87,22 +87,47 @@ The datagenerator protocol class has three main methods:
 
 .. note::
 
-    The :meth:`~f3dasm.datagenerationr.datagenerator.DataGenerator.__call__` method chains these three methods together.
+    The :meth:`~f3dasm.datagenerationr.datagenerator.DataGenerator.run` method chains these three methods together and is inherited from the parent class.
 
 
 In order to create your own data-generator, you need to 
 
-1. inherit from the :class:`~f3dasm.datageneration.datagenerator.DataGenerator` class 
-2. implement at least the :meth:`~f3dasm.datageneration.datagenerator.DataGenerator.execute` method
+1. inherit from the :class:`~f3dasm.datageneration.datagenerator.DataGenerator` class.
+2. implement at least the :meth:`~f3dasm.datageneration.datagenerator.DataGenerator.execute` method, the :meth:`~f3dasm.datageneration.datagenerator.DataGenerator.pre_process` and :meth:`~f3dasm.datageneration.datagenerator.DataGenerator.post_process` are optional.
 
-The :meth:`~f3dasm.datageneration.datagenerator.DataGenerator.execute` method should have the following signature:
+The the :meth:`~f3dasm.datageneration.datagenerator.DataGenerator.pre_process`, :meth:`~f3dasm.datageneration.datagenerator.DataGenerator.execute` and :meth:`~f3dasm.datageneration.datagenerator.DataGenerator.post_process` have to accept arbitrary key-word arguments (:code:`**kwargs`). 
+This is because the :meth:`~f3dasm.datageneration.datagenerator.DataGenerator.run` method will pass any key-word arguments to these methods.
+
+An example is given in the following code block:
 
 .. code-block:: python
 
-    def execute(self, design: f3dasm.Design, **kwargs) -> f3dasm.Design:
-        # do something with the design
-        return design
+    class MySimulator(DataGenerator):
+    def __init__(self, simulator_specific_parameters: Any):
+        self.simulator_specific_parameters = simulator_specific_parameters
+
+    def pre_process(self, any_pre_process_arg: str, **kwargs) -> None:
+        ...
+
+    def execute(self, any_argument: str, **kwargs) -> None:
+        # Retrieve parameters
+        parameter_1 = self.design['parameter1']
+
+        # Run a simulation
+        ...
+
+        # Store the results
+        self.design['result'] = result
+
+    def post_process(self, any_post_process_arg: str, **kwargs) -> None:
+        ...
+
+In order to run this simulator, you need to create an instance of the class and pass it to the :meth:`~f3dasm.design.experimentdata.ExperimentData.run` function:
+
+.. code-block:: python
 
+    simulator = MySimulator(simulator_specific_parameters)
+    experimentdata.run(simulator.run, method='sequential', kwargs={'any_pre_process_arg': 'pre', 'any_argument': 'arg', 'any_post_process_arg': 'post'})
 
 Create a data-generator from a functional approach
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

docs/source/rst_doc_files/general/gettingstarted.rst

@@ -22,10 +22,9 @@ Installing the latest release
 
 :mod:`f3dasm` is purely Python code and compatible with: 
 
-1. Python 3.7 to 3.10. 
+1. Python 3.7 or higher.
 2. the three major operations system (Linux, MacOS, Ubuntu). 
-3. the default environment of Google Colab (Python 3.8, Linux) 
-4. the `pip <https://pypi.org/>`_ package manager system.
+3. the `pip <https://pypi.org/>`_ package manager system.
 
 ----
 
@@ -106,7 +105,6 @@ Installing from source
    -  Studies
    -  Test suite
    -  Documentation source
-   -  Tutorial notebooks
 
 Building from source is required to work on a contribution (bug fix, new feature, code or documentation improvement). We recommend using a `Linux distribution system <https://releases.ubuntu.com/focal/>`_.
 
@@ -123,7 +121,7 @@ Building from source is required to work on a contribution (bug fix, new feature
 
 
 2. Install a recent version of Python (3.7, 3.8, 3.9 or 3.10)
-   for instance using `Miniconda3 <https://docs.conda.io/en/latest/miniconda.html>`_.
+   for instance using `Miniconda3 <https://docs.conda.io/en/latest/miniconda.html>`_. or `Mamba <https://github.com/conda-forge/miniforge#install>`_.
    If you installed Python with conda, we recommend to create a dedicated
    conda environment with all the build dependencies of f3dasm:
 

src/f3dasm/datageneration/datagenerator.py

@@ -21,16 +21,16 @@
 class DataGenerator:
     """Base class for a data generator"""
 
-    def pre_process(self, design: Design, **kwargs) -> None:
+    def pre_process() -> None:
         """Function that handles the pre-processing"""
         ...
         # raise NotImplementedError("No pre-process function implemented!")
 
-    def execute(self, design: Design, **kwargs) -> None:
+    def execute() -> None:
         """Function that calls the FEM simulator the pre-processing"""
         raise NotImplementedError("No execute function implemented!")
 
-    def post_process(self, design: Design, **kwargs) -> None:
+    def post_process() -> None:
         """Function that handles the post-processing"""
         ...
 
@@ -48,7 +48,11 @@ def run(self, design: Design, **kwargs) -> Design:
         Design
             Processed design
         """
-        self.pre_process(design, **kwargs)
-        design = self.execute(design, **kwargs)
-        self.post_process(design, **kwargs)
-        return design
+        # Cache the design
+        self.design: Design = design
+
+        self.pre_process(**kwargs)
+        self.execute(**kwargs)
+        self.post_process(**kwargs)
+
+        return self.design