Moving Window Algorithm

moving_window(signal: ndarray, window_length: int) → ndarray[source]

Perform Moving Window encoding on the input signal.

This function takes a continuous signal and converts it into a spike train using a moving window and threshold-based approach. A spike is generated when the signal exceeds the calculated Base plus or minus a specified Threshold.

Refer to the Moving Window Encoding for a detailed explanation of the Moving Window encoding algorithm.

Code Example:

import numpy as np
from spikify.encoding.temporal.contrast import moving_window
signal = np.array([0.1, 0.3, 0.2, 0.5, 0.8, 1.0])
window_length = 3
encoded_signal = moving_window(signal, window_length)
encoded_signal
Parameters:

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

  • window_length (int) – The size of the sliding window for calculating the base mean.

Returns:

A 1D numpy array representing the encoded spike train.

Return type:

numpy.ndarray

Raises:

  • ValueError – If the input signal is empty.

  • ValueError – If the window length is greater than the length of the signal.

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