Mondaic Documentation
www.mondaic.com
Mondaic
Version:
No results found.
python_api
/
salvus
/
material
/
acoustic
/
hexagonal

salvus.material.acoustic.hexagonal

salvus.material.acoustic.hexagonal salvus material acoustic hexagonal
Hexagonal (VTI) anisotropic acoustic materials.

Classes

TensorComponents

Hexagonal anisotropic acoustic material parametrized by acoustic tensor.
SIGNATURE
class TensorComponents(
    salvus.material.acoustic.hexagonal._Hexagonal,
    salvus.material.acoustic.AcousticTensorComponents,
):
    def __init__(
        self,
        M0: _pd.types.ParameterOrConstantT,
        D11: _pd.types.ParameterOrConstantT,
        D33: _pd.types.ParameterOrConstantT,
        D13: _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.
Required
D33
Type:_pd.types.ParameterOrConstantT
Description:
The d_33 component of the acoustic tensor.
Required
D13
Type:_pd.types.ParameterOrConstantT
Description:
The d_13 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 acoustic constants.
SIGNATURE
def from_params(
    m0: _pd.types.ParameterInput,
    d11: _pd.types.ParameterInput,
    d33: _pd.types.ParameterInput,
    d13: _pd.types.ParameterInput,
) -> typing.Self: ...
ARGUMENTS
Required
m0
Type:_pd.types.ParameterInput
Description:
The density in kg / m^3.
Required
d11
Type:_pd.types.ParameterInput
Description:
The d_11 component of the acoustic tensor.
Required
d33
Type:_pd.types.ParameterInput
Description:
The d_33 component of the acoustic tensor.
Required
d13
Type:_pd.types.ParameterInput
Description:
The d_13 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()
Experimental way to add orientation to a material.
SIGNATURE
def with_orientation(self, orientation: Material | None) -> Material: ...
ARGUMENTS
Required
orientation
Type:Material | None
Description:
The orientation.

Thomsen

Hexagonal acoustic materials specified using Thomsen's parameters.
Salvus' acoustic anisotropic wave equation uses a rank-2 stiffness tensor D_ij (so the squared phase speed is the quadratic form n̂·D·n̂/ρ). Slowness surfaces of that operator are always ellipsoids, while real transversely-isotropic media generally have non-ellipsoidal qP wavefronts. The two coincide exactly only for Thomsen's elliptical case ε = δ.
For ε ≠ δ the simulation produces the closest ellipsoidal fit: an ellipse rotated relative to the symmetry axis (the off-diagonal DHV entry D_13 ∝ δ - ε is what tilts the principal axes), not the true qP wavefront. The same limitation applies in 2D and 3D. Use the elastic anisotropic solver if accurate non-elliptical TI is required.
SIGNATURE
class Thomsen(salvus.material.acoustic.hexagonal._Hexagonal):
    def __init__(
        self,
        RHO: _pd.types.ParameterOrConstantT,
        VP: _pd.types.ParameterOrConstantT,
        DELTA: _pd.types.ParameterOrConstantT,
        EPSILON: _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.
Required
DELTA
Type:_pd.types.ParameterOrConstantT
Description:
Thomsen's delta parameter (dimensionless).
Required
EPSILON
Type:_pd.types.ParameterOrConstantT
Description:
Thomsen's epsilon parameter (dimensionless).

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

Thomsen.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.
Thomsen.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.
Thomsen.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.
Thomsen.from_params()
Construct this material from generic parameters.
SIGNATURE
def from_params(
    rho: _pd.types.ParameterInput,
    vp: _pd.types.ParameterInput,
    delta: _pd.types.ParameterInput,
    epsilon: _pd.types.ParameterInput,
) -> Thomsen: ...
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.
Required
delta
Type:_pd.types.ParameterInput
Description:
Thomsen's delta parameter (dimensionless).
Required
epsilon
Type:_pd.types.ParameterInput
Description:
Thomsen's epsilon parameter (dimensionless).
Thomsen.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,
) -> Thomsen: ...
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.
Thomsen.material_system()
Get the material system of the material.
SIGNATURE
def material_system() -> type[PhysicalMaterial]: ...

Methods

Thomsen.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.
Thomsen.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.
Thomsen.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.
Thomsen.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.
Thomsen.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.
Thomsen.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.
Thomsen.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.
Thomsen.with_orientation()
Experimental way 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

Hexagonal anisotropic elastic material parametrized by velocities.
This material has the same elliptical-only restriction as Thomsen — the implicit Thomsen ε = ½((VPH/VPV)² - 1) enters the same rank-2 D tensor. The simulation is exact when ε = δ and otherwise gives the closest-elliptical fit. See class Thomsen for details.
SIGNATURE
class Velocity(salvus.material.acoustic.hexagonal._Hexagonal):
    def __init__(
        self,
        RHO: _pd.types.ParameterOrConstantT,
        VPV: _pd.types.ParameterOrConstantT,
        VPH: _pd.types.ParameterOrConstantT,
        DELTA: _pd.types.ParameterOrConstantT,
    ) -> None: ...
ARGUMENTS
Required
RHO
Type:_pd.types.ParameterOrConstantT
Description:
Density in kg / m^3.
Required
VPV
Type:_pd.types.ParameterOrConstantT
Description:
Vertical P-wave velocity in m / s.
Required
VPH
Type:_pd.types.ParameterOrConstantT
Description:
Horizontal P-wave velocity in m / s.
Required
DELTA
Type:_pd.types.ParameterOrConstantT
Description:
Thomsen's delta parameter (dimensionless).

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,
    vpv: _pd.types.ParameterInput,
    vph: _pd.types.ParameterInput,
    delta: _pd.types.ParameterInput,
) -> typing.Self: ...
ARGUMENTS
Required
rho
Type:_pd.types.ParameterInput
Description:
Density in kg / m^3.
Required
vpv
Type:_pd.types.ParameterInput
Description:
Vertical P-wave velocity in m / s.
Required
vph
Type:_pd.types.ParameterInput
Description:
Horizontal P-wave velocity in m / s.
Required
delta
Type:_pd.types.ParameterInput
Description:
Thomsen's delta parameter.
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()
Experimental way 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.
Waveform Physics / Materials And Anisotropy / Materials 2: Anisotropy and elliptic coefficients
Previous
elliptical_hexagonal
Next
orthotropic
We use cookies to analyze our traffic, but won't track you until explicit consent is given. Using our contact form will create relevant cookies and transmit data to third party services to keep track of your request. Read more about how we use personal information in our Privacy Policy.
PAGE CONTENTS