Parameter

class glotaran.parameter.parameter.Parameter(label: str = None, full_label: str = None, expression: str | None = None, maximum: float = inf, minimum: float = - inf, non_negative: bool = False, standard_error: float = nan, value: float = nan, vary: bool = True)[source]

Bases: numpy.typing._array_like._SupportsArray

A parameter for optimization.

Optimization Parameter supporting numpy array operations.

Parameters

label (str) – The label of the parameter., by default None
full_label (str) – The label of the parameter with its path in a parameter group prepended. , by default None
expression (str | None) – Expression to calculate the parameters value from, e.g. if used in relation to another parameter. , by default None
maximum (float) – Upper boundary for the parameter to be varied to., by default np.inf
minimum (float) – Lower boundary for the parameter to be varied to., by default -np.inf
non_negative (bool) – Whether the parameter should always be bigger than zero., by default False
standard_error (float) – The standard error of the parameter. , by default np.nan
value (float) – Value of the parameter, by default np.nan
vary (bool) – Whether the parameter should be changed during optimization or not. , by default True

Attributes Summary

`expression`	Expression to calculate the parameters value from.
`full_label`	Label of the parameter with its path in a parameter group prepended.
`label`	Label of the parameter.
`maximum`	Upper bound of the parameter.
`minimum`	Lower bound of the parameter.
`non_negative`	Indicate if the parameter is non-negative.
`standard_error`	Standard error of the optimized parameter.
`transformed_expression`	Expression of the parameter transformed for evaluation within a ParameterGroup.
`value`	Value of the parameter.
`vary`	Indicate if the parameter should be optimized.

Methods Summary

`as_dict`	Create a dictionary containing the parameter properties.
`from_dict`	Create a `Parameter` from a dictionary.
`from_list_or_value`	Create a parameter from a list or numeric value.
`get_value_and_bounds_for_optimization`	Get the parameter value and bounds with expression and non-negative constraints applied.
`markdown`	Get a markdown representation of the parameter.
`set_from_group`	Set all values of the parameter to the values of the corresponding parameter in the group.
`set_value_from_optimization`	Set the value from an optimization result and reverses non-negative transformation.
`valid_label`	Check if a label is a valid label for `Parameter`.

Methods Documentation

as_dict(as_optimized: bool = True) → dict[str, Any][source]: Create a dictionary containing the parameter properties.

property expression: str | None

Expression to calculate the parameters value from.

This can used to set a relation to another parameter.

Returns: The expression.
Return type: str | None

classmethod from_dict(parameter_dict: dict[str, Any]) → Parameter[source]

Create a Parameter from a dictionary.

Expects a dictionary created by :method:`Parameter.as_dict`.

Parameters: parameter_dict (dict[str, Any]) – The source dictionary.
Returns: The created Parameter
Return type: Parameter

classmethod from_list_or_value(value: int | float | list, default_options: dict = None, label: str = None) → Parameter[source]

Create a parameter from a list or numeric value.

Parameters

value (int | float | list) – The list or numeric value.
default_options (dict) – A dictionary of default options.
label (str) – The label of the parameter.

Returns

The created Parameter.

Return type

Parameter

property full_label: str

Label of the parameter with its path in a parameter group prepended.

Returns: The full label.
Return type: str

get_value_and_bounds_for_optimization() → tuple[float, float, float][source]

Get the parameter value and bounds with expression and non-negative constraints applied.

Returns: A tuple containing the value, the lower and the upper bound.
Return type: tuple[float, float, float]

property label: str | None

Label of the parameter.

Returns: The label.
Return type: str

markdown(all_parameters: ParameterGroup | None = None, initial_parameters: ParameterGroup | None = None) → MarkdownStr[source]

Get a markdown representation of the parameter.

Parameters

all_parameters (ParameterGroup | None) – A parameter group containing the whole parameter set (used for expression lookup).
initial_parameters (ParameterGroup | None) – The initial parameter.

Returns

The parameter as markdown string.

Return type

MarkdownStr

property maximum: float

Upper bound of the parameter.

Returns: The upper bound of the parameter.
Return type: float

property minimum: float

Lower bound of the parameter.

Returns: The lower bound of the parameter.
Return type: float

property non_negative: bool

Indicate if the parameter is non-negative.

If true, the parameter will be transformed with $p' = \log{p}$ and $p = \exp{p'}$ .

Notes

Always False if expression is not None.

Returns: Whether the parameter is non-negative.
Return type: bool

set_from_group(group: ParameterGroup)[source]

Set all values of the parameter to the values of the corresponding parameter in the group.

Notes

For internal use.

Parameters: group (ParameterGroup) – The glotaran.parameter.ParameterGroup.

set_value_from_optimization(value: float)[source]

Set the value from an optimization result and reverses non-negative transformation.

Parameters: value (float) – Value from optimization.

property standard_error: float

Standard error of the optimized parameter.

Returns: The standard error of the parameter.
Return type: float

property transformed_expression: str | None

Expression of the parameter transformed for evaluation within a ParameterGroup.

Returns: The transformed expression.
Return type: str | None

static valid_label(label: str) → bool[source]

Check if a label is a valid label for Parameter.

Parameters: label (str) – The label to validate.
Returns: Whether the label is valid.
Return type: bool

property value: float

Value of the parameter.

Returns: The value of the parameter.
Return type: float

property vary: bool

Indicate if the parameter should be optimized.

Notes

Always False if expression is not None.

Returns: Whether the parameter should be optimized.
Return type: bool