November-9th

docs/source/_templates/custom-class-template.rst

@@ -33,4 +33,4 @@
  {% endif %}
  {% endblock %}
 
- .. rubric:: {{ _('Methods') }}
+ .. rubric:: {{ _('Public and private methods') }}

docs/source/conf.py

@@ -14,7 +14,8 @@
 
 sys.path.insert(0, os.path.abspath('../..'))
 sys.path.insert(0, os.path.abspath('../../src'))
-src_dir = [f.path for f in os.scandir(os.path.abspath('../../src/')) if f.is_dir()]
+src_dir = [f.path for f in os.scandir(
+ os.path.abspath('../../src/')) if f.is_dir()]
 for path in src_dir:
  sys.path.insert(0, path)
 
@@ -82,7 +83,7 @@
 # napoleon: https://www.sphinx-doc.org/en/master/usage/extensions/napoleon.html
 napoleon_numpy_docstring = True
 napoleon_include_init_with_doc = True
-napoleon_include_private_with_doc = False
+napoleon_include_private_with_doc = True
 
 # autosummary: https://www.sphinx-doc.org/en/master/usage/extensions/autosummary.html#module-sphinx.ext.autosummary
 autosummary_generate = True

docs/source/rst_doc_files/classes/design/domain.rst

@@ -1,7 +1,34 @@
 Domain and parameters
 =====================
 
-This section will give you information on how to set up your search space with the :ref:`domain <domain>` class and the :ref:`parameter classes <parameters>`
+This section will give you information on how to set up your search space with the :ref:`domain <domain>` class and the :ref:`parameters <parameters>`
+
+
+Domain
+------
+
+.. _domain:
+
+The :class:`~f3dasm.design.Domain` is a set of :class:`f3dasm.design.Parameter` instances that make up the feasible search space.
+
+.. image:: ../../../img/f3dasm-domain.png
+ :width: 100%
+ :align: center
+ :alt: Domain
+
+|
+
+
+To start, we instantiate an empty domain object:
+
+.. code-block:: python
+
+ from f3dasm import Domain
+
+ domain = Domain()
+
+
+Now we can gradually add some parameters!
 
 .. _parameters:
 
@@ -17,107 +44,85 @@ Parameters are singular features of the input search space. They are used to def
 
 |
 
-There are four types of parameters that can be created: :class:`~f3dasm.design.ContinuousParameter`, :class:`~f3dasm.design.DiscreteParameter`, :class:`~f3dasm.design.CategoricalParameter` and :class:`~f3dasm.design.ConstantParameter`:
-
-Continuous Parameter
-^^^^^^^^^^^^^^^^^^^^
-
-* We can create **continous** parameters with a :attr:`~f3dasm.design.ContinuousParameter.lower_bound` and :attr:`~f3dasm.design.ContinuousParameter.upper_bound` with the :class:`~f3dasm.design.ContinuousParameter` class
+There are four types of parameters that can be created: :ref:`float <continuous-parameter>`, :ref:`int <discrete-parameter>`, :ref:`categorical <categorical-parameter>` and :ref:`constant <constant-parameter>` parameters.
 
-.. code-block:: python
-
- x1 = f3dasm.ContinuousParameter(lower_bound=0.0, upper_bound=100.0)
- x2 = f3dasm.ContinuousParameter(lower_bound=0.0, upper_bound=4.0)
+.. _continuous-parameter:
 
-Discrete Parameter
-^^^^^^^^^^^^^^^^^^
+Floating point parameters
+^^^^^^^^^^^^^^^^^^^^^^^^^
 
-* We can create **discrete** parameters with a :attr:`~f3dasm.design.DiscreteParameter.lower_bound` and :attr:`~f3dasm.design.DiscreteParameter.upper_bound` with the :class:`~f3dasm.design.DiscreteParameter` class
+* We can create **continous** parameters with a :code:`low` and :code:`high` boundary with the :meth:`~f3dasm.design.Domain.add_float` method:
 
 .. code-block:: python
 
- x3 = f3dasm.DiscreteParameter(lower_bound=2, upper_bound=4)
- x4 = f3dasm.DiscreteParameter(lower_bound=74, upper_bound=99)
+ domain.add_float(name='x1', low=0.0, high=100.0)
+ domain.add_float(name='x2', low=0.0, high=4.0) 
 
-Categorical Parameter
-^^^^^^^^^^^^^^^^^^^^^
+.. _discrete-parameter:
 
-* We can create **categorical** parameters with a list of items (:attr:`~f3dasm.design.CategoricalParameter.categories`) with the :class:`~f3dasm.design.CategoricalParameter` class
+Discrete parameters
+^^^^^^^^^^^^^^^^^^^
 
-.. code-block:: python
-
- x5 = f3dasm.CategoricalParameter(categories=['test1','test2','test3','test4'])
- x6 = f3dasm.CategoricalParameter(categories=[0.9, 0.2, 0.1, -2])
-
-Constant Parameter
-^^^^^^^^^^^^^^^^^^
-
-* We can create **constant** parameters with any value (:attr:`~f3dasm.design.ConstantParameter.value`) with the :class:`~f3dasm.design.ConstantParameter` class
+* We can create **discrete** parameters with a :code:`low` and :code:`high` boundary with the :meth:`~f3dasm.design.Domain.add_int` method:
 
 .. code-block:: python
 
- x7 = f3dasm.ConstantParameter(value=0.9)
+ domain.add_int(name='x3', low=2, high=4)
+ domain.add_int(name='x4', low=74, high=99) 
 
+.. _categorical-parameter:
 
-Domain
-------
+Categorical parameters
+^^^^^^^^^^^^^^^^^^^^^^
 
-.. _domain:
+* We can create **categorical** parameters with a list of items (:code:`categories`) with the :meth:`~f3dasm.design.Domain.add_category` method:
 
-The :class:`~f3dasm.design.Domain` is a set of :class:`f3dasm.design.Parameter` instances that make up the feasible search space.
+.. code-block:: python
 
-.. image:: ../../../img/f3dasm-domain.png
- :width: 100%
- :align: center
- :alt: Domain
+ domain.add_category(name='x5', categories=['test1','test2','test3','test4'])
+ domain.add_category(name='x6', categories=[0.9, 0.2, 0.1, -2])
 
-|
+.. _constant-parameter:
 
-Domain from a dictionary
-^^^^^^^^^^^^^^^^^^^^^^^^
+Constant parameters
+^^^^^^^^^^^^^^^^^^^
 
-The domain can be constructed by initializing the :class:`~f3dasm.design.Domain` class and 
-providing an attribute (:attr:`~f3dasm.design.Domain.input_space`) containing string names as keys and parameters as values.
+* We can create **constant** parameters with any value (:code:`value`) with the :meth:`~f3dasm.design.Domain.add_constant` method:
 
 .. code-block:: python
 
- from f3dasm import Domain, ContinuousParameter, DiscreteParameter, CategoricalParameter, ConstantParameter
-
- param_1 = f3dasm.ContinuousParameter(lower_bound=-1.0, upper_bound=1.0)
- param_2 = f3dasm.DiscreteParameter(lower_bound=1, upper_bound=10)
- param_3 = f3dasm.CategoricalParameter(categories=['red', 'blue', 'green', 'yellow', 'purple'])
- param_4 = f3dasm.ConstantParameter(value='some_value')
-
- domain = f3dasm.Domain(input_space={'param_1': param_1, 'param_2': param_2, 'param_3': param_3, 'param_4': param_4})
+ domain.add_constant(name='x7', value=0.9)
 
 .. _domain-from-yaml:
 
 Domain from a `hydra <https://hydra.cc/>`_ configuration file
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+-------------------------------------------------------------
 
-If you are using `hydra <https://hydra.cc/>`_ to manage your configuration files, you can create a domain from a configuration file. Your config needs to have the following key:
+If you are using `hydra <https://hydra.cc/>`_ to manage your configuration files, you can create a domain from a configuration file. 
+Your config needs to have a key (e.g. :code:`domain`) that has a dictionary with the parameter names (e.g. :code:`param_1`) as keys 
+and a dictionary with the parameter type (:code:`type`) and the corresponding arguments as values:
 
 .. code-block:: yaml
  :caption: config.yaml
 
  domain:
  param_1:
- _target_: f3dasm.ContinuousParameter
+ type: float
  lower_bound: -1.0
  upper_bound: 1.0
  param_2:
- _target_: f3dasm.DiscreteParameter
+ type: int
  lower_bound: 1
  upper_bound: 10
  param_3:
- _target_: f3dasm.CategoricalParameter
+ type: category
  categories: ['red', 'blue', 'green', 'yellow', 'purple']
  param_4:
- _target_: f3dasm.ConstantParameter
+ type: constant
  value: some_value
 
 
-The same domain can now be created by calling the :func:`~f3dasm.design.Domain.from_yaml` method:
+The domain can now be created by calling the :func:`~f3dasm.design.Domain.from_yaml` method:
 
 .. code-block:: python
 

docs/source/rst_doc_files/classes/optimization/optimizers.rst

@@ -32,8 +32,6 @@ Next, we have to create initial samples. We can use the Latin-hypercube sampler
 
 .. code-block:: python
 
- from f3dasm.sampling import LatinHypercube
-
  data.from_sampling(sampler='latin', domain=domain, n_samples=10, seed=42)
 
 We will use the ``"L-BFGS-B"`` optimizer to find the minimum. For built-in optimizer we can use the name of the optimizer:

docs/source/rst_doc_files/classes/workflow/cluster.rst

@@ -177,7 +177,7 @@ main.py
 
 The `main.py` file is the main entry point of the project. It contains the :mod:`f3dasm` classes and acts on these interfaces.
 It imports :mod:`f3dasm` and the `my_function` from `my_script.py`. 
-In the main function, we create the :class:`~f3dasm.design.domain.Domain`, sample from the :class:`~f3dasm.sampling.latinhypercube.LatinHypercube` sampler , and executes the data generation function (`my_function`) using the :meth:`~f3dasm.design.experimentdata.Experiment.evaluate` method with the specified execution mode.
+In the main function, we create the :class:`~f3dasm.design.domain.Domain`, sample from the Latin Hypercube sampler , and executes the data generation function (`my_function`) using the :meth:`~f3dasm.design.experimentdata.Experiment.evaluate` method with the specified execution mode.
 
 Additionally, the `main.py` file handles which node takes which role.
 

docs/source/rst_doc_files/classes/workflow/hydra.rst

@@ -61,7 +61,6 @@ You can create configurations for each of the :mod:`f3dasm` classes:
 Class Section referencing how to create the `hydra`_ config 
 ============================================================= ======================================================
 :class:`~f3dasm.design.domain.Domain` :ref:`domain-from-yaml` 
-:class:`~f3dasm.sampling.Sampler` :ref:`sampler-hydra` 
 :class:`~f3dasm.design.experimentdata.ExperimentData` :ref:`experimentdata-hydra`
 :class:`~f3dasm.optimization.optimizer.Optimizer` to be implemented!
 :class:`~f3dasm.datageneration.datagenerator.DataGenerator` to be implemented!
@@ -74,13 +73,13 @@ Class Section referencin
 
  domain:
  x0:
- _target_: f3dasm.ContinuousParameter
- lower_bound: 0.0
- upper_bound: 1.0
+ type: float
+ low: 0.0
+ high: 1.0
  x1:
- _target_: f3dasm.ContinuousParameter
- lower_bound: 0.0
- upper_bound: 1.0
+ type: float
+ low: 0.0
+ high: 1.0
 
  experimentdata:
  from_sampling:
@@ -105,7 +104,7 @@ The `main.py` file is the main entry point of the project.
 
 * It imports the necessary modules (`f3dasm`, `hydra`) and the `my_function` from `my_script.py`. 
 * Inside `main.py` script defines a :code:`main` function decorated with :code:`@hydra.main`, which reads the configuration from :code:`config.yaml`. 
-* Within the :code:`main` function, we instantiate the :class:`~f3dasm.design.domain.Domain`, sample from the :class:`~f3dasm.sampling.latinhypercube.LatinHypercube` sampler , and executes the data generation function (`my_function`) using the :meth:`~f3dasm.design.experimentdata.Experiment.run` method with the specified execution mode.
+* Within the :code:`main` function, we instantiate the :class:`~f3dasm.design.domain.Domain`, sample from the Lating Hypercube sampler , and executes the data generation function (`my_function`) using the :meth:`~f3dasm.design.experimentdata.Experiment.run` method with the specified execution mode.
 
 
 

src/f3dasm/__init__.py

@@ -18,13 +18,9 @@
 from ._src import _imports as _imports
 from ._src._argparser import HPC_JOBID
 from ._src._imports import try_import
-from ._src.design.domain import Domain, make_nd_continuous_domain
-from ._src.design.parameter import (CategoricalParameter, ConstantParameter,
- ContinuousParameter, DiscreteParameter)
 from ._src.experimentdata.experimentdata import ExperimentData
 from ._src.experimentdata.experimentsample import ExperimentSample
 from ._src.logger import DistributedFileHandler, logger
-from ._src.optimization.optimizer import Optimizer
 from ._src.run_optimization import (OptimizationResult, calculate_mean_std,
  run_multiple_realizations,
  run_optimization)
@@ -47,28 +43,16 @@
 __all__ = [
  'datageneration',
  'design',
- 'machinelearning',
  'optimization',
- 'sampling',
- 'Domain',
- 'make_nd_continuous_domain',
  'ExperimentData',
- 'CategoricalParameter',
- 'ConstantParameter',
- 'ContinuousParameter',
- 'DiscreteParameter',
+ 'ExperimentSample',
  'DistributedFileHandler',
  'logger',
- 'Optimizer',
  'run_on_experimentdata',
  'run_operation_on_experiments',
  'OptimizationResult',
  'run_multiple_realizations',
- 'run_multiple_realizations_to_disk',
  'run_optimization',
- 'run_optimization_to_disk',
- 'Sampler',
- 'ExperimentSample',
  'HPC_JOBID',
  'try_import',
  'calculate_mean_std',

src/f3dasm/_src/datageneration/abaqus/abaqus_simulator.py

@@ -45,8 +45,8 @@ def __init__(self, name: str = "job", num_cpus: int = 1,
  Set true if you want to delete the temporary files after
  post-processing, by default True
 
- Notes
- -----
+ Note
+ ----
  The kwargs are saved as attributes to the class. This is useful for the
  simulation script to access the parameters.
  """