Mondaic DocumentationRequired
QKAPPA| Type: | _pd.types.ParameterOrConstantT |
| Description: | Q for the bulk modulus. |
Version:
2026.5.0
Salvus documentation version
2026.5.0
2025.1.3
2024.1.3
0.12.16
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salvus.material.visco.acoustic
salvus.material.visco.acoustic salvus material visco acousticViscoacoustic materials.
Classes
Canonical
An elastic material parameterized by density and p-wave velocity.
SIGNATURE
class Canonical(salvus.material.visco.acoustic._ViscoAcousticMaterial):
def __init__(self, QKAPPA: _pd.types.ParameterOrConstantT) -> None: ...ARGUMENTS
Properties
- ds(
typing.Mapping)-Material's xarray representation. - flatten(
dict)-Get all parameters as a dict.
Class Methods
Canonical.from_dataset()
Construct a material from an xarray Dataset.
SIGNATURE
def from_dataset(ds: xr.Dataset) -> Material[_pd.types.ParameterFlavorT]: ...ARGUMENTS
Required
ds| Type: | xr.Dataset |
| Description: | The dataset to construct the material from. |
Canonical.from_json()
Recreate the object from a dictionary serialization of its
initialization parameters.
SIGNATURE
def from_json(d: builtins.dict) -> Any: ...ARGUMENTS
Required
d| Type: | builtins.dict |
| Description: | Dictionary containing its init parameters and a few other things. |
Canonical.from_material()
Construct this material from another within the same physical system.
SIGNATURE
def from_material(
m: Material[_pd.types.ParameterFlavorT],
reduction_method: Literal["remove-components", "force"] | None = None,
) -> Canonical[_pd.types.ParameterFlavorT]: ...ARGUMENTS
Required
m| Type: | Material[_pd.types.ParameterFlavorT] |
| Description: | Material to transform. |
Optional
reduction_method| Type: | Literal['remove-components', 'force'] | None |
| Default value: | None |
| Description: | Method to move between incompatible symmetry classes. None will only move to symmetries that are equal or more permissive, while remove-components will drop components that are found to match the new material's constraints as necessary, and thus leading to loss of free parameters but not of information. The option "force" will take all information necessary to construct the new parameter set without verification, leading to loss of information. |
Canonical.from_params()
Construct this material from generic parameters.
SIGNATURE
def from_params(qkappa: _pd.types.ParameterInput) -> Self: ...ARGUMENTS
Required
qkappa| Type: | _pd.types.ParameterInput |
| Description: | Q for the bulk modulus. |
Canonical.material_system()
Method that will return the material system of material.
SIGNATURE
def material_system() -> type[Material]: ...Methods
Canonical.map()
Generic map for dataclass instances.
f should be a function taking two parameters: the name of the
dataclass member and its value, and it should return a tuple containing
the same quantities. If a member is not to be transformed, f should
just return a tuple of the input member name and value, unchanged. Both
names and values can be transformed, with the semantics following those
of dataclasses.replace.In Salvus we primarily treat dataclasses as containers offering
semantics similar to typed dictionaries. Deriving from this protocol
allows any relevant dataclass to additionally be treated functorially.
This allows for the generic un- and re-wrapping of value held in
dataclasses, and essentially replaces the following imperative code:
@dataclass class A: member: int # Before my_a = A(member=1) my_a_new = dataclasses.replace(my_a, member=2 * my_a.member) # After my_a_new = A(val=1).map(lambda key, val: (key, 2 * val))
As with many functional patterns, the perceived benefits for simple
demonstrative purposes is minimal. The scalability of this pattern
becomes apparent, however, when parsing deeply nested abstractions, as
the transformation logic can be factored out into independent
functions. This is used extensively, for example, in the realization
logic of the layered mesher, where generic materials can have generic
parameters, etc.
SIGNATURE
def map(
self, f: typing.Callable[[str, typing.Any], tuple[str, typing.Any]]
) -> typing.Self: ...ARGUMENTS
Required
f| Type: | typing.Callable[[str, typing.Any], tuple[str, typing.Any]] |
| Description: | The function to map over the dataclass. |
Canonical.map_realized_parameters()
Apply functions to each parameter individually, distinguishing _pd.
Useful when one wants to transform each parameter type separately. For
instance, transformations of discrete parameters often require more
associated logic than their constant equivalents. This function
abstracts away the boilerplate of check for each parameter type, and
subsequently transforming it with some function, as well as ensuring
that the parameters are indeed of the correct realized type.
The signatures of each transformation function should take the
parameter's name and value as two distinct inputs, and return the
(potentially modified) parameter value.
SIGNATURE
def map_realized_parameters(
self,
f_constant: typing.Callable[
[str, _pd.realized.constant.Parameter], _pd.realized.constant.Parameter
] = salvus.material.base_materials._map_realized_default,
f_discrete: typing.Callable[
[str, _pd.realized.discrete.Parameter], _pd.realized.discrete.Parameter
] = salvus.material.base_materials._map_realized_default,
f_analytic: typing.Callable[
[str, _pd.realized.analytic.Parameter], _pd.realized.analytic.Parameter
] = salvus.material.base_materials._map_realized_default,
) -> Self: ...ARGUMENTS
Optional
f_constant| Type: | typing.Callable[[str, _pd.realized.constant.Parameter], _pd.realized.constant.Parameter] |
| Default value: | salvus.material.base_materials._map_realized_default |
| Description: | The function to apply to constant parameters. Defaults to returning the parameter as-is. |
Optional
f_discrete| Type: | typing.Callable[[str, _pd.realized.discrete.Parameter], _pd.realized.discrete.Parameter] |
| Default value: | salvus.material.base_materials._map_realized_default |
| Description: | The function to apply to discrete parameters. Defaults to returning the parameter as-is. |
Optional
f_analytic| Type: | typing.Callable[[str, _pd.realized.analytic.Parameter], _pd.realized.analytic.Parameter] |
| Default value: | salvus.material.base_materials._map_realized_default |
| Description: | The function to apply to analytic parameters. Defaults to returning the parameter as-is. |
Canonical.qc_test()
Run a series of material quality control tests.
The function also prints a summary of the issues found, including their
severity and any mitigation steps that can be taken.
SIGNATURE
def qc_test(
self,
level: validation.QCLevel | str = QCLevel.strict,
display_issues: bool = True,
) -> dict[str, MaterialQCIssue]: ...ARGUMENTS
Optional
level| Type: | validation.QCLevel | str |
| Default value: | QCLevel.strict |
| Description: | The level of quality control to perform. The BASIC level performs minimal checks, while the STRICT level performs more thorough checks that are potentially slow. One can pass an enumeration value or a string representation of the level. |
Optional
display_issues| Type: | bool |
| Default value: | True |
| Description: | If True, prints the issues found during the quality control checks. If False, issues are collected but not printed. |
Canonical.to_json()
Serialize the object to a dictionary that can be written to JSON.
SIGNATURE
def to_json(
self,
external_file_hash: types = None,
timer: types = None,
log_to_logger: bool = False,
comm: types = None,
) -> builtins.dict: ...ARGUMENTS
Optional
external_file_hash| Type: | types |
| Default value: | None |
| Description: | Hash of any external files associated with this object. Can be passed here in which case it will be stored in a centralized location in the JSON file. |
Optional
timer| Type: | types |
| Default value: | None |
| Description: | Execution timer. |
Optional
log_to_logger| Type: | bool |
| Default value: | False |
| Description: | Log timings to the logger. |
Optional
comm| Type: | types |
| Default value: | None |
| Description: | MPI communicator, if any. |
Canonical.to_wavelength_oracle()
The wavelength oracle.
SIGNATURE
def to_wavelength_oracle(
self, n_dim: typing.Literal[2, 3] | None = None
) -> _pd.types.ParameterOrConstantT: ...ARGUMENTS
Optional
n_dim| Type: | typing.Literal[2, 3] | None |
| Default value: | None |
| Description: | Dimension to return the oracle for, deprecated. |
Canonical.with_orientation()
Experimetal method to add orientation to a material.
SIGNATURE
def with_orientation(self, orientation: Material | None) -> Material: ...ARGUMENTS
Required
orientation| Type: | Material | None |
| Description: | The orientation. |
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