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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 classbase_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 - 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
.. 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?
- 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:
-
Push to the pypi branch. This executes the tests on circleci.com
-
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