Mondaic DocumentationRequired
RHO| Type: | _pd.types.ParameterOrConstantT |
| Description: | The density in kg / m^3. |
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.acoustic.isotropic
salvus.material.acoustic.isotropic salvus material acoustic isotropicIsotropic acoustic materials.
Classes
BulkModulus
Isotropic acoustic material parametrized by its Bulk Modulus.
SIGNATURE
class BulkModulus(salvus.material.acoustic.isotropic._Isotropic):
def __init__(
self,
RHO: _pd.types.ParameterOrConstantT,
KAPPA: _pd.types.ParameterOrConstantT,
) -> None: ...ARGUMENTS
Required
KAPPA| Type: | _pd.types.ParameterOrConstantT |
| Description: | The bulk modulus in Pascals. |
Properties
- ds(
typing.Mapping)-Material's xarray representation. - flatten(
dict)-Get all parameters as a dict. - viscosity(
Material | None)-Get the optional attenuation.
Class Methods
BulkModulus.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. |
BulkModulus.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. |
BulkModulus.from_material()
Construct this material from another within the same physical system.
SIGNATURE
def from_material(
m: Material[_pd.types.ParameterFlavorT],
reduction_method: (
typing.Literal["remove-components", "force"] | None
) = None,
) -> PhysicalMaterial[_pd.types.ParameterFlavorT]: ...ARGUMENTS
Required
m| Type: | Material[_pd.types.ParameterFlavorT] |
| Description: | Material to transform. |
Optional
reduction_method| Type: | typing.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. |
BulkModulus.from_params()
Construct this material from generic parameters.
SIGNATURE
def from_params(
rho: _pd.types.ParameterInput, kappa: _pd.types.ParameterInput
) -> typing.Self: ...ARGUMENTS
Required
rho| Type: | _pd.types.ParameterInput |
| Description: | The density in kg / m^3. |
Required
kappa| Type: | _pd.types.ParameterInput |
| Description: | The bulk modulus in Pascals. |
BulkModulus.from_tensor_components()
Create material from tensor components acoustic parameter material.
Overwrite this method if your material can not be constructed from
acoustic constants.
A class method to create a anisotropic material of a desired symmetry
class from a canonical TC material. The method will automatically check
if the canonical material that is passed meets the symmetry
requirements of the desired materials. If it does not, a TypeError will
be raised.
SIGNATURE
def from_tensor_components(
m: GenericTensorComponents[_pd.types.ParameterFlavorT],
reduction_method: (
typing.Literal["remove-components", "force"] | None
) = None,
) -> typing.Self: ...ARGUMENTS
Required
m| Type: | GenericTensorComponents[_pd.types.ParameterFlavorT] |
| Description: | The material in tensor components parametrization to be used to construct the new material. |
Optional
reduction_method| Type: | typing.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. |
BulkModulus.material_system()
Get the material system of the material.
SIGNATURE
def material_system() -> type[PhysicalMaterial]: ...Methods
BulkModulus.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. |
BulkModulus.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. |
BulkModulus.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. |
BulkModulus.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. |
BulkModulus.to_tensor_components()
Generate a tensor component representation of the material.
This method ensures compatibility with solver and other symmetries.
SIGNATURE
def to_tensor_components(
self, expand_symmetries: bool = False
) -> MaterialDict | GenericTensorComponents: ...ARGUMENTS
Optional
expand_symmetries| Type: | bool |
| Default value: | False |
| Description: | boolean determining if to return a expanded canonical parameters instead of the TensorComponents object in the relevant symmetry system. Defaults to False. |
BulkModulus.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. |
BulkModulus.with_attenuation()
Add attenuation to an object.
SIGNATURE
def with_attenuation(self, attenuation: Material | None) -> Self: ...ARGUMENTS
Required
attenuation| Type: | Material | None |
| Description: | The attenuation material. |
BulkModulus.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. |
LinearCoefficients
An acoustic material parameterized by it's elliptical constants.
Essentially the same as the tensor components material, but with a scalar
instead of an acoustic tensor.
SIGNATURE
class LinearCoefficients(salvus.material.acoustic.isotropic._Isotropic):
def __init__(
self,
M0: _pd.types.ParameterOrConstantT,
M1: _pd.types.ParameterOrConstantT,
) -> None: ...ARGUMENTS
Required
M0| Type: | _pd.types.ParameterOrConstantT |
| Description: | The M0 parameter. |
Required
M1| Type: | _pd.types.ParameterOrConstantT |
| Description: | The M1 parameter. |
Properties
- ds(
typing.Mapping)-Material's xarray representation. - flatten(
dict)-Get all parameters as a dict. - viscosity(
Material | None)-Get the optional attenuation.
Class Methods
LinearCoefficients.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. |
LinearCoefficients.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. |
LinearCoefficients.from_material()
Construct this material from another within the same physical system.
SIGNATURE
def from_material(
m: Material[_pd.types.ParameterFlavorT],
reduction_method: (
typing.Literal["remove-components", "force"] | None
) = None,
) -> PhysicalMaterial[_pd.types.ParameterFlavorT]: ...ARGUMENTS
Required
m| Type: | Material[_pd.types.ParameterFlavorT] |
| Description: | Material to transform. |
Optional
reduction_method| Type: | typing.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. |
LinearCoefficients.from_params()
Construct this material from generic parameters.
SIGNATURE
def from_params(
m0: _pd.types.ParameterInput, m1: _pd.types.ParameterInput
) -> typing.Self: ...ARGUMENTS
Required
m0| Type: | _pd.types.ParameterInput |
| Description: | The M0 parameter. |
Required
m1| Type: | _pd.types.ParameterInput |
| Description: | The M1 parameter. |
LinearCoefficients.from_tensor_components()
Create material from tensor components acoustic parameter material.
Overwrite this method if your material can not be constructed from
acoustic constants.
A class method to create a anisotropic material of a desired symmetry
class from a canonical TC material. The method will automatically check
if the canonical material that is passed meets the symmetry
requirements of the desired materials. If it does not, a TypeError will
be raised.
SIGNATURE
def from_tensor_components(
m: GenericTensorComponents[_pd.types.ParameterFlavorT],
reduction_method: (
typing.Literal["remove-components", "force"] | None
) = None,
) -> typing.Self: ...ARGUMENTS
Required
m| Type: | GenericTensorComponents[_pd.types.ParameterFlavorT] |
| Description: | The material in tensor components parametrization to be used to construct the new material. |
Optional
reduction_method| Type: | typing.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. |
LinearCoefficients.material_system()
Get the material system of the material.
SIGNATURE
def material_system() -> type[PhysicalMaterial]: ...Methods
LinearCoefficients.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. |
LinearCoefficients.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. |
LinearCoefficients.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. |
LinearCoefficients.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. |
LinearCoefficients.to_tensor_components()
Generate a tensor component representation of the material.
This method ensures compatibility with solver and other symmetries.
SIGNATURE
def to_tensor_components(
self, expand_symmetries: bool = False
) -> MaterialDict | GenericTensorComponents: ...ARGUMENTS
Optional
expand_symmetries| Type: | bool |
| Default value: | False |
| Description: | boolean determining if to return a expanded canonical parameters instead of the TensorComponents object in the relevant symmetry system. Defaults to False. |
LinearCoefficients.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. |
LinearCoefficients.with_attenuation()
Add attenuation to an object.
SIGNATURE
def with_attenuation(self, attenuation: Material | None) -> Self: ...ARGUMENTS
Required
attenuation| Type: | Material | None |
| Description: | The attenuation material. |
LinearCoefficients.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. |
TensorComponents
Isotropic acoustic material parametrized by elastic constant in its tensor
representation.
SIGNATURE
class TensorComponents(
salvus.material.acoustic.isotropic._Isotropic,
salvus.material.acoustic.AcousticTensorComponents,
):
def __init__(
self,
M0: _pd.types.ParameterOrConstantT,
D11: _pd.types.ParameterOrConstantT,
) -> None: ...ARGUMENTS
Required
M0| Type: | _pd.types.ParameterOrConstantT |
| Description: | The density in kg / m^3. |
Required
D11| Type: | _pd.types.ParameterOrConstantT |
| Description: | The d_11 component of the acoustic tensor. |
Properties
- ds(
typing.Mapping)-Material's xarray representation. - flatten(
dict)-Get all parameters as a dict. - viscosity(
Material | None)-Get the optional attenuation.
Class Methods
TensorComponents.all_components()
Get all components.
SIGNATURE
def all_components() -> list[str]: ...TensorComponents.equal_components()
Get equal components for a material class.
SIGNATURE
def equal_components() -> dict[str, str]: ...TensorComponents.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. |
TensorComponents.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. |
TensorComponents.from_material()
Construct this material from another within the same physical system.
SIGNATURE
def from_material(
m: Material[_pd.types.ParameterFlavorT],
reduction_method: (
typing.Literal["remove-components", "force"] | None
) = None,
) -> PhysicalMaterial[_pd.types.ParameterFlavorT]: ...ARGUMENTS
Required
m| Type: | Material[_pd.types.ParameterFlavorT] |
| Description: | Material to transform. |
Optional
reduction_method| Type: | typing.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. |
TensorComponents.from_params()
Construct a hexagonal material from elastic constants.
SIGNATURE
def from_params(
m0: _pd.types.ParameterInput, d11: _pd.types.ParameterInput
) -> typing.Self: ...ARGUMENTS
Required
m0| Type: | _pd.types.ParameterInput |
| Description: | The M0 parameter. |
Required
d11| Type: | _pd.types.ParameterInput |
| Description: | The d_11 component of the acoustic tensor. |
TensorComponents.from_tensor_components()
Create material from tensor components acoustic parameter material.
Overwrite this method if your material can not be constructed from
acoustic constants.
A class method to create a anisotropic material of a desired symmetry
class from a canonical TC material. The method will automatically check
if the canonical material that is passed meets the symmetry
requirements of the desired materials. If it does not, a TypeError will
be raised.
SIGNATURE
def from_tensor_components(
m: GenericTensorComponents[_pd.types.ParameterFlavorT],
reduction_method: (
typing.Literal["remove-components", "force"] | None
) = None,
) -> Self: ...ARGUMENTS
Required
m| Type: | GenericTensorComponents[_pd.types.ParameterFlavorT] |
| Description: | The material in tensor components parametrization to be used to construct the new material. |
Optional
reduction_method| Type: | typing.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. |
TensorComponents.material_system()
Get the material system of the material.
SIGNATURE
def material_system() -> type[PhysicalMaterial]: ...TensorComponents.nonzero_components()
Get nonzero components for a material class.
SIGNATURE
def nonzero_components() -> list[str]: ...TensorComponents.zero_components()
Get zero components for a material class.
SIGNATURE
def zero_components() -> list[str]: ...Methods
TensorComponents.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. |
TensorComponents.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. |
TensorComponents.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. |
TensorComponents.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. |
TensorComponents.to_tensor_components()
Generate a tensor component representation of the material.
This method ensures compatibility with solver and other symmetries.
SIGNATURE
def to_tensor_components(
self, expand_symmetries: bool = False
) -> MaterialDict | GenericTensorComponents: ...ARGUMENTS
Optional
expand_symmetries| Type: | bool |
| Default value: | False |
| Description: | boolean determining if to return a expanded canonical parameters instead of the TensorComponents object in the relevant symmetry system. Defaults to False. |
TensorComponents.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. |
TensorComponents.with_attenuation()
Add attenuation to an object.
SIGNATURE
def with_attenuation(self, attenuation: Material | None) -> Self: ...ARGUMENTS
Required
attenuation| Type: | Material | None |
| Description: | The attenuation material. |
TensorComponents.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. |
Velocity
An acoustic material parameterized by density and p-wave velocity.
SIGNATURE
class Velocity(salvus.material.acoustic.isotropic._Isotropic):
def __init__(
self,
RHO: _pd.types.ParameterOrConstantT,
VP: _pd.types.ParameterOrConstantT,
) -> None: ...ARGUMENTS
Required
RHO| Type: | _pd.types.ParameterOrConstantT |
| Description: | Density in kg / m^3. |
Required
VP| Type: | _pd.types.ParameterOrConstantT |
| Description: | P-wave velocity in m / s. |
Properties
- ds(
typing.Mapping)-Material's xarray representation. - flatten(
dict)-Get all parameters as a dict. - viscosity(
Material | None)-Get the optional attenuation.
Class Methods
Velocity.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. |
Velocity.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. |
Velocity.from_material()
Construct this material from another within the same physical system.
SIGNATURE
def from_material(
m: Material[_pd.types.ParameterFlavorT],
reduction_method: (
typing.Literal["remove-components", "force"] | None
) = None,
) -> PhysicalMaterial[_pd.types.ParameterFlavorT]: ...ARGUMENTS
Required
m| Type: | Material[_pd.types.ParameterFlavorT] |
| Description: | Material to transform. |
Optional
reduction_method| Type: | typing.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. |
Velocity.from_params()
Construct this material from generic parameters.
SIGNATURE
def from_params(
rho: _pd.types.ParameterInput, vp: _pd.types.ParameterInput
) -> typing.Self: ...ARGUMENTS
Required
rho| Type: | _pd.types.ParameterInput |
| Description: | Density in kg / m^3. |
Required
vp| Type: | _pd.types.ParameterInput |
| Description: | P-wave velocity in m / s. |
Velocity.from_tensor_components()
Create material from tensor components acoustic parameter material.
Overwrite this method if your material can not be constructed from
acoustic constants.
A class method to create a anisotropic material of a desired symmetry
class from a canonical TC material. The method will automatically check
if the canonical material that is passed meets the symmetry
requirements of the desired materials. If it does not, a TypeError will
be raised.
SIGNATURE
def from_tensor_components(
m: GenericTensorComponents[_pd.types.ParameterFlavorT],
reduction_method: (
typing.Literal["remove-components", "force"] | None
) = None,
) -> typing.Self: ...ARGUMENTS
Required
m| Type: | GenericTensorComponents[_pd.types.ParameterFlavorT] |
| Description: | The material in tensor components parametrization to be used to construct the new material. |
Optional
reduction_method| Type: | typing.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. |
Velocity.material_system()
Get the material system of the material.
SIGNATURE
def material_system() -> type[PhysicalMaterial]: ...Methods
Velocity.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. |
Velocity.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. |
Velocity.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. |
Velocity.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. |
Velocity.to_tensor_components()
Generate a tensor component representation of the material.
This method ensures compatibility with solver and other symmetries.
SIGNATURE
def to_tensor_components(
self, expand_symmetries: bool = False
) -> MaterialDict | GenericTensorComponents: ...ARGUMENTS
Optional
expand_symmetries| Type: | bool |
| Default value: | False |
| Description: | boolean determining if to return a expanded canonical parameters instead of the TensorComponents object in the relevant symmetry system. Defaults to False. |
Velocity.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. |
Velocity.with_attenuation()
Add attenuation to an object.
SIGNATURE
def with_attenuation(self, attenuation: Material | None) -> Self: ...ARGUMENTS
Required
attenuation| Type: | Material | None |
| Description: | The attenuation material. |
Velocity.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. |
Used in tutorials
Functionality from this module is used in the following tutorials.
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