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.generic_model
salvus.opt.models.generic_model salvus opt models generic_modelA generic model based on a numpy array.
Classes
GenericModel
Generic inversion model using a numpy array.
SIGNATURE
class GenericModel(salvus.opt.models.base_model.BaseModel):
def __init__(self, name: str, data: str | pathlib.Path | npt.NDArray): ...ARGUMENTS
Required
data| Type: | str | pathlib.Path | npt.NDArray |
| Description: | Model data. |
Properties
- data(
npt.NDArray)-The model data as an arbitrary numpy array. - model(
npt.NDArray)-The model as its actual representation. - name(
str)-Model name. - status(
ModelStatus)-Model status to keep track of whether the model has been modified. - vector(
npt.NDArray)-The model data as a vector. Returns: vector: The model data flattened to a 1D array.
Class Methods
GenericModel.from_disk()
Load a model from disk. This will use the dictionary and path provided.
SIGNATURE
def from_disk(parent_folder: pathlib.Path, d: dict) -> GenericModel: ...ARGUMENTS
Required
parent_folder| Type: | pathlib.Path |
| Description: | Path to store the model. |
Required
d| Type: | dict |
| Description: | Dictionary containing meta information of the model. |
GenericModel.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
GenericModel.compute_inf_norm()
Infinity norm of the model.
SIGNATURE
def compute_inf_norm(self) -> float: ...GenericModel.compute_norm()
Return the model norm.
SIGNATURE
def compute_norm(self) -> float: ...GenericModel.copy()
Copy the model.
SIGNATURE
def copy(self, name: str) -> GenericModel: ...ARGUMENTS
Required
name| Type: | str |
| Description: | Name of the new (copied) model. |
GenericModel.dot()
Dot product of the model with another model.
SIGNATURE
def dot(self, other: GenericModel) -> float: ...ARGUMENTS
Required
other| Type: | GenericModel |
| Description: | The other model. |
GenericModel.max()
In-place point-wise maximum.
SIGNATURE
def max(self, other: GenericModel) -> GenericModel: ...ARGUMENTS
Required
other| Type: | GenericModel |
| Description: | Model to compare with. |
GenericModel.min()
In-place point-wise minimum.
SIGNATURE
def min(self, other: GenericModel) -> GenericModel: ...ARGUMENTS
Required
other| Type: | GenericModel |
| Description: | Model to compare with. |
GenericModel.to_disk()
Serialize the model to JSON (and an associated npy file).
SIGNATURE
def to_disk(self, parent_folder: pathlib.Path | str) -> dict: ...ARGUMENTS
Required
parent_folder| Type: | pathlib.Path | str |
| Description: | Parent folder where the JSON + npy files should be stored. |
GenericModel.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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