mvpa2.kernels.np.RbfKernel

class mvpa2.kernels.np.RbfKernel(*args, **kwargs)

Radial basis function (aka Gausian, aka ) kernel K(a,b) = exp(-||a-b||**2/sigma)

Methods

add_conversion(typename, methodfull, methodraw)	Adds methods to the Kernel class for new conversions :Parameters: typename : string Describes kernel type methodfull : function Method which converts to the new kernel object class methodraw : function Method which returns a raw kernel ..
as_ls(kernel)
as_np()	Converts this kernel to a Numpy-based representation
as_raw_ls(kernel)
as_raw_np()	Directly return this kernel as a numpy array.
cleanup()	Wipe out internal representation
compute(ds1[, ds2])	Generic computation of any kernel Assumptions: - ds1, ds2 are either datasets or arrays, - presumably 2D (not checked neither enforced here - _compute takes ndarrays.
computed(*args, **kwargs)	Compute kernel and return self
reset()

Base Kernel class has no parameters

Methods

add_conversion(typename, methodfull, methodraw)	Adds methods to the Kernel class for new conversions :Parameters: typename : string Describes kernel type methodfull : function Method which converts to the new kernel object class methodraw : function Method which returns a raw kernel ..
as_ls(kernel)
as_np()	Converts this kernel to a Numpy-based representation
as_raw_ls(kernel)
as_raw_np()	Directly return this kernel as a numpy array.
cleanup()	Wipe out internal representation
compute(ds1[, ds2])	Generic computation of any kernel Assumptions: - ds1, ds2 are either datasets or arrays, - presumably 2D (not checked neither enforced here - _compute takes ndarrays.
computed(*args, **kwargs)	Compute kernel and return self
reset()