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**********
sfsimodels
**********
A set of python objects to represent physical objects for assessing structural and geotechnical problems
Attempting to solve the `Liskov Substitution Principle <https://en.wikipedia.org/wiki/Liskov_substitution_principle>`_
problem for combining independently developed source
code in the fields of structural and geotechnical engineering.
Models represent states of physical objects, currently can not represent dynamic/changing states.
Model inheritance system
========================
Every object contains a ``type``, a ``base_type`` and a list of ``ancestor_types``.
- ``type`` is the current type of the class or instance of the class
- ``base_type`` is what class should be considered as for standard operations such as saving and loading.
- ``ancestor_types`` is a list of the ``type`` of the ancestors of the class
Generation of new custom models
===============================
It is easiest to create a new object by inheriting from ``sm.CustomObject``, as this contains the default parameters
needed for loading and saving the model.
If you chose not to use the default custom object, you must set the object ``base_type`` parameter to ``"custom_object"``.
Loading a custom object
=======================
pass a dictionary to the ``custom_object`` parameter in the ``sm.load_json`` function, where the dictionary contains:
`custom={"<base_type>-<type>": Object}`.
Installation
============
.. code:: bash
pip install sfsimodels
Citing
======
Please use the following citation:
Millen M. D. L. (2019) Sfsimodels <version-number> - A set of standard models for assessing structural and geotechnical problems,
https://pypi.org/project/sfsimodels/, doi: 10.5281/zenodo.2596721
Saving and loading models
=========================
Check out a full set of examples [on github](https://github.com/eng-tools/sfsimodels/blob/master/examples/saving_and_loading_objects.ipynb)
.. code-block:: python
structure = models.Structure() # Create a structure object
structure.id = 1 # Assign it an id
structure.name = "sample building" # Assign it a name and other parameters
structure.h_eff = 10.0
structure.t_fixed = 1.0
structure.mass_eff = 80000.
structure.mass_ratio = 1.0 # Set vertical and horizontal masses are equal
ecp_output = files.Output() # Create an output object
ecp_output.add_to_dict(structure) # Add the structure to the output object
ecp_output.name = "test data"
ecp_output.units = "N, kg, m, s" # Set the units
ecp_output.comments = ""
p_str = json.dumps(ecp_output.to_dict(), skipkeys=["__repr__"], indent=4) # Assign it to a json string
objs = files.loads_json(p_str) # Load a json string and convert to a dictionary of objects
assert ct.isclose(structure.mass_eff, objs['buildings'][1].mass_eff) # Access the object
How do I get set up?
====================
1. Run ``pip install -r requirements.txt``
Testing
=======
Tests are run with pytest
* Locally run: ``pytest`` on the command line.
* Tests are run on every push using travis, see the ``.travis.yml`` file
Deployment
==========
To deploy the package to pypi.com you need to:
1. Push to the *pypi* branch. This executes the tests on circleci.com
2. Create a git tag and push to github, run: ``trigger_deploy.py`` or manually:
.. code:: bash
git tag 0.5.2 -m "version 0.5.2"
git push --tags origin pypi
Contributing
============
* All properties that require exterior parameters should be named ``get_<property>``,
* Parameters that vary with depth in the soil profile should be named ``get_<property>_at_depth``
* Properties in the stress dependent soil should use ``get_<property>_at_v_eff_stress`` to obtain the property
* Functions that set properties on objects should start with 'set' then the property the citation, i.e. ``set_<property>_<author-year>``
* Methods that generate properties on the object should have the prefix ``gen_`` then property i.e. ``gen_<property`` e.g. ``soil_profile.gen_split()``
Documentation
=============
At http://sfsimodels.readthedocs.io/en/latest/
Known bugs
==========
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