smash.Model.set_serr_sigma_parameters#

Model.set_serr_sigma_parameters(key, value)[source]#

Set the values of a Model structural error sigma parameter.

This method performs an in-place operation on the Model object.

Parameters:

keystr: The name of the structural error sigma parameter.
valuefloat or numpy.ndarray: The value(s) to set to the structural error sigma parameter. If the value is a numpy.ndarray, its shape must be broadcastable into the structural error sigma parameter shape.

See also

Model.get_serr_sigma_parameters: Get the values of a Model structural error sigma parameter.
Model.serr_sigma_parameters: Model structural error sigma parameters.

Examples

>>> from smash.factory import load_dataset
>>> setup, mesh = load_dataset("cance")
>>> model = smash.Model(setup, mesh)

Set a specific value to a structural error sigma parameter vector

>>> model.set_serr_sigma_parameters("sg0", 2)

Access its value

>>> model.get_serr_sigma_parameters("sg0")
array([2., 2., 2.], dtype=float32)

Set a vector with a shape equivalent to the structural error sigma parameter

Get the structural error sigma parameter size (equivalent to the number of gauge model.mesh.ng)

>>> size = model.get_serr_sigma_parameters("sg0").size
>>> size
3

Generate the vector

>>> vec = np.arange(1, size + 1)
>>> vec
array([1, 2, 3])

Set to the structural error sigma parameter the vector

>>> model.set_serr_sigma_parameters("sg0", vec)
>>> model.get_serr_sigma_parameters("sg0")
array([1., 2., 3.], dtype=float32)

Note

This method is equivalent to directly slicing the serr_sigma_parameters.values array (as shown below) and change the values but is simpler and safer to use.

Access the structual error sigma parameter keys

>>> model.serr_sigma_parameters.keys
array(['sg0', 'sg1'], dtype='<U3')

Get the index of the structural error sigma parameter 'sg0'

>>> ind = np.argwhere(model.serr_sigma_parameters.keys == "sg0").item()
>>> ind
0

Slice the serr_sigma_parameters.values array on the last axis and change its values

>>> model.serr_sigma_parameters.values[..., ind] = 0.5
>>> model.serr_sigma_parameters.values[..., ind]
array([[0.5, 0.5, 0.5]], dtype=float32)

Warning

In that case, there’s no problem to set the value 0.5 to the structural error sigma parameter 'sg0', but each structural error sigma parameter has a feasibility domain, and that outside this domain, the model cannot run. For example, the feasibility domain of 'sg0' is \(]0, +\inf[\).

Trying to set a negative value to the strutural error sigma parameter 'sg0' without the setter

>>> model.serr_sigma_parameters.values[..., ind] = -1
>>> model.serr_sigma_parameters.values[..., ind]
array([[-1., -1., -1.]], dtype=float32)

No particular problem doing this but trying with the setter

>>> model.set_serr_sigma_parameters("sg0", -1)
ValueError: Invalid value for model serr_sigma_parameter 'sg0'. serr_sigma_parameter domain [-1, -1]
is not included in the feasible domain ]0, inf[

Finally, trying to run the Model with a negative value set to the structural error sigma parameter 'sg0' leads to the same error

>>> model.forward_run()
ValueError: Invalid value for model serr_sigma_parameter 'sg0'. serr_sigma_parameter domain [-1, -1]
is not included in the feasible domain ]0, inf[