braintools.input.Smoothed

class braintools.input.Smoothed(input_obj, tau)

Exponentially smoothed version of an input.

Applies exponential smoothing (low-pass filtering) to an input, useful for removing sharp transitions or high-frequency noise.

Parameters:

• input_obj (Input) – The input to smooth.

• tau (float | Quantity) – Smoothing time constant. Larger values give more smoothing.

Notes

Implements exponential smoothing: y[t] = alpha * x[t] + (1 - alpha) * y[t-1] where alpha = dt / tau.

The cutoff frequency is approximately 1 / (2 * pi * tau).

Examples

>>> # Sharp steps
>>> steps = Step([0, 1, 0.5, 1, 0],
...                   [0, 50, 100, 150, 200],
...                   250 * u.ms)
>>>
>>> # Light smoothing (fast response)
>>> light = Smoothed(steps, 5 * u.ms)
>>>
>>> # Heavy smoothing (slow response)
>>> heavy = Smoothed(steps, 25 * u.ms)
>>>
>>> # Usually created via smooth() method
>>> smooth = steps.smooth(10 * u.ms)

__init__(input_obj, tau)

Initialize smoothed input.

Parameters:

• input_obj (Input) – The input to smooth.

• tau (float | Quantity) – Smoothing time constant.

Methods

__init__(input_obj, tau)	Initialize smoothed input.
apply(func)	Apply a custom function to the input.
clip([min_val, max_val])	Clip the input values to a range.
generate()	Generate the smoothed input.
repeat(n_times)	Repeat the input pattern n times.
scale(factor)	Scale the input by a factor.
shift(time_shift)	Shift the input in time.
smooth(tau)	Apply exponential smoothing to the input.

Attributes

dt	Get the time step from global environment.
n_steps	Get the number of time steps.
shape	Get the shape of the input array.