Note
Click here to download the full example code
Overview of the MockModel for load case LC1¶
A toy model implementing an unphysical analytical law; used for testing purpose
from __future__ import annotations
from vimseo import EXAMPLE_RUNS_DIR
from vimseo.api import create_model
from vimseo.core.model_settings import IntegratedModelSettings
Out:
<frozen importlib._bootstrap>:241: DeprecationWarning: builtin type SwigPyPacked has no __module__ attribute
<frozen importlib._bootstrap>:241: DeprecationWarning: builtin type SwigPyObject has no __module__ attribute
<frozen importlib._bootstrap>:241: DeprecationWarning: builtin type swigvarlink has no __module__ attribute
/home/sebastien.bocquet/PycharmProjects/vimseo/.tox/doc/lib/python3.11/site-packages/pydantic/_internal/_config.py:291: PydanticDeprecatedSince20: Support for class-based `config` is deprecated, use ConfigDict instead. Deprecated in Pydantic V2.0 to be removed in V3.0. See Pydantic V2 Migration Guide at https://errors.pydantic.dev/2.9/migration/
warnings.warn(DEPRECATION_MESSAGE, DeprecationWarning)
Detected plugins: []
2026-05-11 16:51:27.316 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager
2026-05-11 16:51:27.317 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager
/home/sebastien.bocquet/PycharmProjects/vimseo/.tox/doc/lib/python3.11/site-packages/pydantic/_internal/_generate_schema.py:547: UserWarning: <module 'openturns.dist' from '/home/sebastien.bocquet/PycharmProjects/vimseo/.tox/doc/lib/python3.11/site-packages/openturns/dist.py'> is not a Python type (it may be an instance of an object), Pydantic will allow any object with no validation since we cannot even enforce that the input is an instance of the given type. To get rid of this error wrap the type with `pydantic.SkipValidation`.
warn(
/home/sebastien.bocquet/PycharmProjects/vimseo/.tox/doc/lib/python3.11/site-packages/pydantic/_internal/_generate_schema.py:547: UserWarning: <built-in function array> is not a Python type (it may be an instance of an object), Pydantic will allow any object with no validation since we cannot even enforce that the input is an instance of the given type. To get rid of this error wrap the type with `pydantic.SkipValidation`.
warn(
First, let's instantiate the model for a given load case:
model_name = "MockModel"
load_case = "LC1"
model = create_model(
model_name,
load_case,
check_subprocess=True,
model_options=IntegratedModelSettings(
directory_archive_root=EXAMPLE_RUNS_DIR / "archive/model_gallery",
directory_scratch_root=EXAMPLE_RUNS_DIR / "scratch/model_gallery",
cache_file_path=EXAMPLE_RUNS_DIR
/ f"caches/model_gallery/{model_name}_{load_case}_cache.hdf",
),
)
Out:
2026-05-11 16:51:29.367 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager
2026-05-11 16:51:29.759 WARNING streamlit.runtime.caching.cache_data_api: No runtime found, using MemoryCacheStorageManager
INFO - 16:51:30: Found 1 entries in the cache file : /home/sebastien.bocquet/PycharmProjects/vimseo/docs/runnable_examples/model_runs/caches/model_gallery/MockModel_LC1_cache.hdf node : node
The model description can be accessed like this:
print(model.description)
Out:
Model MockModel: A toy model implementing an unphysical analytical law; used for testing purpose
Load case:
Load case LC1: A first mock load case.
Boundary condition variables:
[]
Plot parameters:
{
"curves": []
}
Load:
Load(direction='', sign='', type='')
Default values:
Default geometrical variables:
{"x1": [0.1], "x1_maximum_only": [0.1], "x1_minimum_only": [0.1], "x1_no_bounds": [0.1]}
Default numerical variables:
{}
Default boundary conditions variables:
{}
Default material variables:
{}
model_inputs:
[
"x1",
"x1_maximum_only",
"x1_minimum_only",
"x1_no_bounds"
]
model_outputs:
[
"y1",
"error_code",
"model",
"load_case",
"description",
"job_name",
"persistent_result_files",
"n_cpus",
"date",
"cpu_time",
"user",
"machine",
"vims_git_version",
"directory_archive_root",
"directory_archive_job",
"directory_scratch_root",
"directory_scratch_job"
]
An illustration of the load case:
model.show_image()
The model is executed with its default input values:
model.execute()
Out:
{'x1': array([0.1]), 'x1_maximum_only': array([0.1]), 'x1_minimum_only': array([0.1]), 'x1_no_bounds': array([0.1]), 'cpu_time': array([0.01094174]), 'date': array(['2026-03-26 14:43:28.324130'], dtype='<U26'), 'description': array([''], dtype='<U1'), 'directory_archive_job': array(['/home/sebastien.bocquet/PycharmProjects/vimseo/docs/runnable_examples/model_runs/archive/model_gallery/MockModel/LC1/2'],
dtype='<U118'), 'directory_archive_root': array(['/home/sebastien.bocquet/PycharmProjects/vimseo/docs/runnable_examples/model_runs/archive/model_gallery'],
dtype='<U102'), 'directory_scratch_job': array([''], dtype='<U1'), 'directory_scratch_root': array(['/home/sebastien.bocquet/PycharmProjects/vimseo/docs/runnable_examples/model_runs/scratch/model_gallery'],
dtype='<U102'), 'error_code': array([0]), 'job_name': array([''], dtype='<U1'), 'load_case': array(['LC1'], dtype='<U3'), 'machine': array(['IPF7101'], dtype='<U7'), 'model': array(['MockModel'], dtype='<U9'), 'n_cpus': array([1]), 'persistent_result_files': array([''], dtype='<U1'), 'user': array(['sebastien.bocquet'], dtype='<U17'), 'vims_git_version': array(['d0050d8de498c8354552cdde540fb3e524454871'], dtype='<U40'), 'y1': array([5.2])}
And the results are visualised with the pre-defined plots:
figures = model.plot_results(show=True)
Out:
INFO - 16:51:30: Saving plots to /home/sebastien.bocquet/PycharmProjects/vimseo/docs/runnable_examples/01_models
Total running time of the script: ( 0 minutes 6.102 seconds)
Download Python source code: plot_MockModel_LC1.py