Kernels

Definition of a hierarchy of classes for kernel functions to be used in convolution, e.g., for data smoothing (low pass filtering) or firing rate estimation.

Symmetric kernels

RectangularKernel(sigma[, invert]) Class for rectangular kernels.
TriangularKernel(sigma[, invert]) Class for triangular kernels.
EpanechnikovLikeKernel(sigma[, invert]) Class for Epanechnikov-like kernels.
GaussianKernel(sigma[, invert]) Class for gaussian kernels.
LaplacianKernel(sigma[, invert]) Class for laplacian kernels.

Asymmetric kernels

ExponentialKernel(sigma[, invert]) Class for exponential kernels.
AlphaKernel(sigma[, invert]) Class for alpha kernels.

Examples

>>> import quantities as pq
>>> kernel1 = GaussianKernel(sigma=100*pq.ms)
>>> kernel2 = ExponentialKernel(sigma=8*pq.ms, invert=True)