elephant.kernels.AlphaKernel¶
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class
elephant.kernels.AlphaKernel(sigma, invert=False)[source]¶ Class for alpha kernels.

with
.For the alpha kernel an analytical expression for the boundary of the integral as a function of the area under the alpha kernel function cannot be given. Hence in this case the value of the boundary is determined by kernel-approximating numerical integration, inherited from the Kernel class.
Attributes: min_cutofffloatHalf width of the kernel.
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__call__(self, t)¶ Evaluates the kernel at all points in the array t.
Parameters: - tpq.Quantity
Vector with the interval on which the kernel is evaluated, not necessarily a time interval.
Returns: - pq.Quantity
Vector with the result of the kernel evaluations.
Raises: - TypeError
If t is not pq.Quantity.
If the dimensionality of t and
sigmaare different.
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boundary_enclosing_area_fraction(self, fraction)¶ Calculates the boundary
so that the integral from
to
encloses a certain fraction of the
integral over the complete kernel.By definition the returned value is hence non-negative, even if the whole probability mass of the kernel is concentrated over negative support for inverted kernels.
Returns: - pq.Quantity
Boundary of the kernel containing area fraction under the kernel density.
Raises: - ValueError
If fraction was chosen too close to one, such that in combination with integral approximation errors the calculation of a boundary was not possible.
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is_symmetric(self)¶ In the case of symmetric kernels, this method is overwritten in the class SymmetricKernel, where it returns True, hence leaving the here returned value False for the asymmetric kernels.
Returns: - bool
True in classes SymmetricKernel, RectangularKernel, TriangularKernel, EpanechnikovLikeKernel, GaussianKernel, and LaplacianKernel. False in classes Kernel, ExponentialKernel, and AlphaKernel.
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property
min_cutoff¶ Half width of the kernel.
Returns: - float
The returned value varies according to the kernel type.