Param_Observational

class obsidian.parameters.continuous.Param_Observational(name: str, min: int | float, max: int | float, search_min: int | float | None = None, search_max: int | float | None = None, design_point: int | float | None = None)

Bases: Param_Continuous

This is an observational numeric variable that is used for fitting but is not leveraged during optimization

name

The name of the parameter.

Type:

str

min

The minimum value of the parameter.

Type:

int or float

max

The maximum value of the parameter.

Type:

int or float

design_point

The point which the observational value will be locked to during experiment optimization

Type:

int or float

__init__(name: str, min: int | float, max: int | float, search_min: int | float | None = None, search_max: int | float | None = None, design_point: int | float | None = None)

Methods

__init__(name, min, max[, search_min, ...])
decode(X)	Decode parameter from transformed space
encode(X)	Encode parameter to a format that can be used for training
load_state(obj_dict)	Load the state of the Parameter object from a dictionary.
open_search()	Set the search space to the parameter space
save_state()	Save the state of the Parameter object.
set_search(search_min, search_max)	Set the search space for the parameter
unit_demap(X)
unit_map(X)

Attributes

range

The range of the parameter (max - min)