Contrast Decoder

contrast_decoder(spikes: ndarray, thresholds: ndarray, start_point: float | int | list[float | int] | ndarray) → ndarray[source]

Perform Contrast family decoding on the input spike train.

This function takes a spike train encoded with any of the Contrast family algorithms, Threshold-Based Representation (TBR), Step-Forward (SF), Moving Window (MW) or Zero-Crossing Step-Forward (ZCSF), and reconstructs the original continuous signal. The reconstruction is performed by starting from the initial signal value and applying the threshold incrementally based on the spike values.

Note

  • The thresholds parameter should be the thresholds array returned directly by the encoder (TBR, SF, or MW). All three encoders return this array as part of their output to ensure the step size used for reconstruction exactly matches the one used during encoding.

  • The start_point parameter should be set to the first sample of the original signal prior to encoding (e.g. signal[0] for a 1D signal, or signal[0, :] for a multi-feature/channel signal). Since the Contrast family encodes only differences between consecutive samples, the absolute signal level is lost during encoding and must be restored by anchoring reconstruction to this initial value.

Code Example:

import numpy as np
from spikify.encoders.temporal.contrast import moving_window
from spikify.decoders.temporal.contrast import contrast_decoder

signal = np.array([0.1, 0.3, 0.2, 0.5, 0.8, 1.0])
window_length = 3
spikes, thresholds = moving_window(signal, window_length, threshold=0.2)
reconstructed_signal = contrast_decoder(spikes, thresholds, start_point=signal[0])
Parameters:

  • spikes (numpy.ndarray) – The input spike train to be decoded. This should be a numpy ndarray with values in {-1, 0, +1}, as produced by any of the Contrast family encoders (TBR, SF, MW, ZCSF).

  • threshold (numpy.ndarray) – Per-feature or channels threshold values used during encoding, as returned directly by the TBR, SF, MW or ZCSF encoder. Passing the encoder’s returned thresholds array ensures the reconstruction step size exactly matches the one used during encoding.

  • start_point (float | int | list[float | int] | numpy.ndarray) – Initial signal value(s) for reconstruction (scalar or 1D sequence matching features). Should be set to the first sample of the original signal before encoding (e.g. signal[0]), as the Contrast family encodes only signal differences and the absolute offset must be restored manually.

Returns:

A numpy array representing the reconstructed continuous signal approximation.

Return type:

numpy.ndarray

Raises:

ValueError – If the input spike train is empty or if the start_point dimensions do not match the spike train feature dimensions.