Mondaic DocumentationRequired
name| Type: | str |
| Description: | Name of the model. |
Version:
2026.5.0
Salvus documentation version
2026.5.0
2025.1.3
2024.1.3
0.12.16
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salvus.opt.models.structured_model
salvus.opt.models.structured_model salvus opt models structured_modelA structured model class based on xarray Datasets.
Classes
StructuredModel
Structured inversion model based on xarray DataSets.
SIGNATURE
class StructuredModel(salvus.opt.models.base_model.BaseModel):
def __init__(
self,
name: str,
model: str | pathlib.Path | xr.Dataset,
fields: list[str],
): ...ARGUMENTS
Required
model| Type: | str | pathlib.Path | xr.Dataset |
| Description: | xarray DataSet. |
Required
fields| Type: | list[str] |
| Description: | Names of the elemental fields to use. |
Properties
- model(
xr.Dataset)-The model as its actual representation. - name(
str)-Model name. - status(
ModelStatus)-Model status to keep track of whether the model has been modified.
Class Methods
StructuredModel.from_disk()
Load a model from disk.
SIGNATURE
def from_disk(parent_folder: pathlib.Path, d: dict) -> StructuredModel: ...ARGUMENTS
Required
parent_folder| Type: | pathlib.Path |
| Description: | Path where the model is stored. |
Required
d| Type: | dict |
| Description: | Dictionary containing meta information of the model. |
StructuredModel.from_json()
Create a model from a dictionary.
SIGNATURE
def from_json(d: dict) -> Self: ...ARGUMENTS
Required
d| Type: | dict |
| Description: | Dictionary containing meta information of the model. |
Methods
StructuredModel.compute_inf_norm()
Infinity norm of the model.
SIGNATURE
def compute_inf_norm(self) -> float: ...StructuredModel.compute_norm()
Return the model norm.
SIGNATURE
def compute_norm(self) -> float: ...StructuredModel.copy()
Copy the model.
SIGNATURE
def copy(self, name: str) -> StructuredModel: ...ARGUMENTS
Required
name| Type: | str |
| Description: | Name of the new (copied) model. |
StructuredModel.dot()
Dot product of the model with another model.
SIGNATURE
def dot(self, other: StructuredModel) -> float: ...ARGUMENTS
Required
other| Type: | StructuredModel |
| Description: | The other model. |
StructuredModel.max()
In-place point-wise maximum.
SIGNATURE
def max(self, other: StructuredModel) -> StructuredModel: ...ARGUMENTS
Required
other| Type: | StructuredModel |
| Description: | Model to compare with. |
StructuredModel.min()
In-place point-wise minimum.
SIGNATURE
def min(self, other: StructuredModel) -> StructuredModel: ...ARGUMENTS
Required
other| Type: | StructuredModel |
| Description: | Model to compare with. |
StructuredModel.to_disk()
Serialize the model to disk. This will use the model name and the path
provided. Heavy data are written directly to disk, light data are
returned as dictionary.
SIGNATURE
def to_disk(self, parent_folder: pathlib.Path | str) -> dict: ...ARGUMENTS
Required
parent_folder| Type: | pathlib.Path | str |
| Description: | Path to store the model. |
StructuredModel.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. |
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