quant_met.parameters.Parameters#

class quant_met.parameters.Parameters(*, control, k_points)#

Class to hold the parameters for a calculation.

Attributes:
controlControl

An instance of the Control class containing settings for the calculation.

model

An instance of one of the Hamiltonian parameter classes, holding the specific parameters of the selected Hamiltonian model.

k_pointsKPoints

An instance of the KPoints class that specifies the number of k-points for the simulation.

Methods

copy(*[, include, exclude, update, deep])

Returns a copy of the model.

model_construct([_fields_set])

Creates a new instance of the Model class with validated data.

model_copy(*[, update, deep])

!!! abstract "Usage Documentation"

model_dump(*[, mode, include, exclude, ...])

!!! abstract "Usage Documentation"

model_dump_json(*[, indent, ensure_ascii, ...])

!!! abstract "Usage Documentation"

model_json_schema([by_alias, ref_template, ...])

Generates a JSON schema for a model class.

model_parametrized_name(params)

Compute the class name for parametrizations of generic classes.

model_post_init(context, /)

Override this method to perform additional initialization after __init__ and model_construct.

model_rebuild(*[, force, raise_errors, ...])

Try to rebuild the pydantic-core schema for the model.

model_validate(obj, *[, strict, extra, ...])

Validate a pydantic model instance.

model_validate_json(json_data, *[, strict, ...])

!!! abstract "Usage Documentation"

model_validate_strings(obj, *[, strict, ...])

Validate the given object with string data against the Pydantic model.

construct

dict

from_orm

json

parse_file

parse_obj

parse_raw

schema

schema_json

update_forward_refs

validate