Note
Click here to download the full example code
Overview of the MockCurvesXRange for load case Dummy¶
from __future__ import annotations
from vimseo import EXAMPLE_RUNS_DIR
from vimseo.api import create_model
from vimseo.core.model_settings import IntegratedModelSettings
First, let's instantiate the model for a given load case:
model_name = "MockCurvesXRange"
load_case = "Dummy"
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",
),
)
The model description can be accessed like this:
print(model.description)
Out:
Model MockCurvesXRange:
Load case:
Load case Dummy: A dummy load case.
Boundary condition variables:
[]
Plot parameters:
{
"curves": []
}
Load:
Load(direction='', sign='', type='')
Default values:
Default geometrical variables:
{"x_left": [-0.5], "x_right": [0.5], "y_max": [1.0]}
Default numerical variables:
{}
Default boundary conditions variables:
{}
Default material variables:
{}
model_inputs:
[
"x_left",
"x_right",
"y_max"
]
model_outputs:
[
"x_left",
"x_right",
"y_axis",
"y",
"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:
{'x_left': array([-0.5]), 'x_right': array([0.5]), 'y_max': array([1.]), 'cpu_time': array([1.85438347]), 'date': array(['2025-11-05 22:19:51.413435'], dtype='<U26'), 'description': array([''], dtype='<U1'), 'directory_archive_job': array(['..\\model_runs\\archive\\model_gallery\\MockCurvesXRange\\Dummy\\1'],
dtype='<U60'), 'directory_archive_root': array(['C:\\Users\\sebastien.bocquet\\PycharmProjects\\vims\\docs\\runnable_examples\\model_runs\\archive\\model_gallery'],
dtype='<U103'), 'directory_scratch_job': array([''], dtype='<U1'), 'directory_scratch_root': array(['C:\\Users\\sebastien.bocquet\\PycharmProjects\\vims\\docs\\runnable_examples\\model_runs\\scratch\\model_gallery'],
dtype='<U103'), 'error_code': array([0]), 'job_name': array([''], dtype='<U1'), 'load_case': array(['Dummy'], dtype='<U5'), 'machine': array(['B20191729'], dtype='<U9'), 'model': array(['MockCurvesXRange'], dtype='<U16'), 'n_cpus': array([1]), 'persistent_result_files': array([''], dtype='<U1'), 'user': array(['sebastien.bocquet'], dtype='<U17'), 'vims_git_version': array(['95990fa211debd91a91ffe1d89b2b0b4b855f387'], dtype='<U40'), 'y': array([4.99223491e-01, 4.80104069e-01, 4.61190193e-01, 4.42504527e-01,
4.24068265e-01, 4.05901175e-01, 3.88021655e-01, 3.70446778e-01,
3.53192344e-01, 3.36272932e-01, 3.19701952e-01, 3.03491697e-01,
2.87653389e-01, 2.72197236e-01, 2.57132480e-01, 2.42467444e-01,
2.28209582e-01, 2.14365527e-01, 2.00941134e-01, 1.87941527e-01,
1.75371140e-01, 1.63233761e-01, 1.51532568e-01, 1.40270170e-01,
1.29448643e-01, 1.19069560e-01, 1.09134027e-01, 9.96427143e-02,
9.05958775e-02, 8.19933888e-02, 7.38347566e-02, 6.61191462e-02,
5.88453963e-02, 5.20120329e-02, 4.56172794e-02, 3.96590627e-02,
3.41350144e-02, 2.90424673e-02, 2.43784445e-02, 2.01396407e-02,
1.63223933e-02, 1.29226389e-02, 9.93585077e-03, 7.35694796e-03,
5.18016101e-03, 3.39882650e-03, 2.00505438e-03, 9.89139398e-04,
3.38357018e-04, 3.36837598e-05, 3.54172010e-05, 3.55769622e-04,
1.04004269e-03, 2.10823879e-03, 3.57373695e-03, 5.44674104e-03,
7.73554550e-03, 1.04471536e-02, 1.35876267e-02, 1.71622995e-02,
2.11759202e-02, 2.56327453e-02, 3.05366039e-02, 3.58909420e-02,
4.16988515e-02, 4.79630884e-02, 5.46860818e-02, 6.18699362e-02,
6.95164275e-02, 7.76269944e-02, 8.62027254e-02, 9.52443412e-02,
1.04752174e-01, 1.14726146e-01, 1.25165736e-01, 1.36069958e-01,
1.47437323e-01, 1.59265805e-01, 1.71552805e-01, 1.84295110e-01,
1.97488850e-01, 2.11129455e-01, 2.25211612e-01, 2.39729210e-01,
2.54675297e-01, 2.70042025e-01, 2.85820598e-01, 3.02001218e-01,
3.18573030e-01, 3.35524066e-01, 3.52841188e-01, 3.70510029e-01,
3.88514937e-01, 4.06838915e-01, 4.25463565e-01, 4.44369031e-01,
4.63533940e-01, 4.82935348e-01, 5.02548687e-01, 5.22347711e-01]), 'y_axis': array([-0.5 , -0.48989899, -0.47979798, -0.46969697, -0.45959596,
-0.44949495, -0.43939394, -0.42929293, -0.41919192, -0.40909091,
-0.3989899 , -0.38888889, -0.37878788, -0.36868687, -0.35858586,
-0.34848485, -0.33838384, -0.32828283, -0.31818182, -0.30808081,
-0.2979798 , -0.28787879, -0.27777778, -0.26767677, -0.25757576,
-0.24747475, -0.23737374, -0.22727273, -0.21717172, -0.20707071,
-0.1969697 , -0.18686869, -0.17676768, -0.16666667, -0.15656566,
-0.14646465, -0.13636364, -0.12626263, -0.11616162, -0.10606061,
-0.0959596 , -0.08585859, -0.07575758, -0.06565657, -0.05555556,
-0.04545455, -0.03535354, -0.02525253, -0.01515152, -0.00505051,
0.00505051, 0.01515152, 0.02525253, 0.03535354, 0.04545455,
0.05555556, 0.06565657, 0.07575758, 0.08585859, 0.0959596 ,
0.10606061, 0.11616162, 0.12626263, 0.13636364, 0.14646465,
0.15656566, 0.16666667, 0.17676768, 0.18686869, 0.1969697 ,
0.20707071, 0.21717172, 0.22727273, 0.23737374, 0.24747475,
0.25757576, 0.26767677, 0.27777778, 0.28787879, 0.2979798 ,
0.30808081, 0.31818182, 0.32828283, 0.33838384, 0.34848485,
0.35858586, 0.36868687, 0.37878788, 0.38888889, 0.3989899 ,
0.40909091, 0.41919192, 0.42929293, 0.43939394, 0.44949495,
0.45959596, 0.46969697, 0.47979798, 0.48989899, 0.5 ])}
And the results are visualised with the pre-defined plots:
figures = model.plot_results(show=True)
Out:
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Plot of y_vs_y_axis
figures["y_vs_y_axis"]
Total running time of the script: ( 0 minutes 0.097 seconds)
Download Python source code: plot_MockCurvesXRange_Dummy.py
Download Jupyter notebook: plot_MockCurvesXRange_Dummy.ipynb