SpectralModel
- class glotaran.builtin.models.spectral.spectral_model.SpectralModel[source]
Bases:
glotaran.model.base_model.Model
Attributes Summary
The type of the model as human readable string.
Methods Summary
Creates a model from a dictionary.
Formats the model as Markdown string.
Returns a list with all problems in the model and missing parameters if specified.
Simulates the model.
Returns True if the number problems in the model is 0, else False
Returns a string listing all problems in the model and missing parameters if specified.
Methods Documentation
- add_weights(item: glotaran.model.weight.Weight)
- additional_penalty_function = None
- constrain_matrix_function = None
- property dataset: Dict[str, glotaran.builtin.models.kinetic_image.kinetic_image_dataset_descriptor.KineticImageDatasetDescriptor]
- classmethod from_dict(model_dict_ref: dict) glotaran.model.base_model.Model
Creates a model from a dictionary.
- Parameters
model_dict – Dictionary containing the model.
- get_dataset(label) glotaran.builtin.models.kinetic_image.kinetic_image_dataset_descriptor.KineticImageDatasetDescriptor
- get_megacomplex(label) glotaran.model.decorator._set_megacomplexes.<locals>.MetaMegacomplex
- get_shape(label) glotaran.builtin.models.spectral.shape.SpectralShape
- global_dimension = 'time'
- global_matrix = None
- grouped()
- has_additional_penalty_function = None
- has_matrix_constraints_function = None
- index_dependent()
- markdown(parameters: Optional[glotaran.parameter.parameter_group.ParameterGroup] = None, initial_parameters: Optional[glotaran.parameter.parameter_group.ParameterGroup] = None, base_heading_level: int = 1) glotaran.utils.ipython.MarkdownStr
Formats the model as Markdown string.
Parameters will be included if specified.
- Parameters
parameter (ParameterGroup) – Parameter to include.
initial_parameters (ParameterGroup) – Initial values for the parameters.
base_heading_level (int) –
Base heading level of the markdown sections.
E.g.:
If it is 1 the string will start with ‘# Model’.
If it is 3 the string will start with ‘### Model’.
- property megacomplex: Dict[str, glotaran.model.decorator._set_megacomplexes.<locals>.MetaMegacomplex]
- model_dimension = 'spectral'
- problem_list(parameters: ParameterGroup = None) list[str]
Returns a list with all problems in the model and missing parameters if specified.
- Parameters
parameter – The parameter to validate.
- retrieve_clp_function = None
- set_dataset(label, item: glotaran.builtin.models.kinetic_image.kinetic_image_dataset_descriptor.KineticImageDatasetDescriptor)
- set_megacomplex(label, item: glotaran.model.decorator._set_megacomplexes.<locals>.MetaMegacomplex)
- set_shape(label, item: glotaran.builtin.models.spectral.shape.SpectralShape)
- property shape: Dict[str, glotaran.builtin.models.spectral.shape.SpectralShape]
- simulate(dataset: str, parameters: ParameterGroup, axes: dict[str, np.ndarray] = None, clp: np.ndarray | xr.DataArray = None, noise: bool = False, noise_std_dev: float = 1.0, noise_seed: int = None) xr.Dataset
Simulates the model.
- Parameters
dataset – Label of the dataset to simulate.
parameter – The parameters for the simulation.
axes – A dictionary with axes for simulation.
clp – Conditionally linear parameters. Used instead of model.global_matrix if provided.
noise – If True noise is added to the simulated data.
noise_std_dev – The standard deviation of the noise.
noise_seed – Seed for the noise.
- valid(parameters: Optional[glotaran.parameter.parameter_group.ParameterGroup] = None) bool
Returns True if the number problems in the model is 0, else False
- Parameters
parameter – The parameter to validate.
- validate(parameters: Optional[glotaran.parameter.parameter_group.ParameterGroup] = None) str
Returns a string listing all problems in the model and missing parameters if specified.
- Parameters
parameter – The parameter to validate.
- property weights: Dict[str, glotaran.model.weight.Weight]