TaskSettingsMixin

TaskSettingsMixin dataclass

TaskSettingsMixin(
    *,
    fix_intensity: float = 0,
    fix_time: int | tuple[int, int] = 100,
    iti: int | tuple[int, int] = 0,
    dt: int = 20,
    tau: int = 100,
    n_outputs: int = 2,
    output_behavior: list[float] = lambda: [0, 1](),
    noise_std: float = 0.01,
    scaling: bool = True
)

Mixin data class defining detailed parameters for Task.

These settings are expected to be maintained throughout most experiments, whereas the attributes of Task itself are expected to be more commonly adjusted between individual experiments.

Parameters:

Name	Type	Description	Default
fix_intensity	float	Intensity of input signal during fixation. Defaults to 0.	0
fix_time	int | tuple[int, int]	Fixation time in ms. If a tuple is given, it is interpreted as an interval of possible values, and for each trial the value will be randomly picked from it. Note that the duration of each input and output signal is increased by this time. Defaults to 100.	100
iti	int | tuple[int, int]	Inter-trial interval, or time window between sequential trials, in ms. If a tuple is given, it is interpreted as an interval of possible values, and for each trial the value will be randomly picked from it. Defaults to 0.	0
dt	int	Sampling interval (inverted sampling frequency) in ms. Defaults to 20.	20
tau	int	Time constant for the dynamics of each network node in ms. Defaults to 100.	100
n_outputs	int	Number of output nodes in the network, signaling different behavioral choices. Defaults to 2.	2
output_behavior	list[float]	List of possible intensity values of the behavioral output. Currently only the smallest and largest value of this list are used. Defaults to [0, 1].	lambda: [0, 1]()
noise_std	float	Standard deviation of input noise. Defaults to 0.01.	0.01
scaling	bool	If True, input and output signals are rescaled between 0 and 1. A MinMaxScaler logic is used for this purpose. Defaults to True.	True