Step Forward Algorithm

step_forward(signal: ndarray, threshold: float | list[float]) → ndarray[source]

Perform Step-Forward encoding on the input signal.

This function takes a continuous signal and converts it into a spike train using a dynamically updated baseline and threshold-based approach. A spike is generated when the signal exceeds or drops below the dynamically adjusted baseline (Base) by the specified Threshold.

Refer to the Step Forward Encoding for a detailed explanation of the Step-Forward encoding algorithm.

Code Example:

import numpy as np
from spikify.encoding.temporal.contrast import step_forward
signal = np.array([0.1, 0.3, 0.4, 0.2, 0.5, 0.6])
threshold = 0.2
encoded_signal = step_forward(signal, threshold)
Parameters:

  • signal (numpy.ndarray) – The input signal to be encoded. This should be a numpy ndarray.

  • threshold (float | list[float]) – The threshold value(s) for spike detection. Can be a float or a list of floats.

Returns:

A numpy array representing the encoded spike train.

Return type:

numpy.ndarray

Raises:

  • ValueError – If the input signal is empty.

  • TypeError – If the signal is not a numpy ndarray.