kernel.py 文件源码

def kernel_dist(kernel=linear, **kw):
    """Generic kernel-induced distance metric.

    To use, `partially` apply this function with a kernel argument.

    Examples
    --------
    >>> from functools import partial
    >>> dist = partial(kernel_dist, kernel=sigmoid)
    """
    if kernel is None:  # Don't use a kernel!
        return dist.euclidean
    elif getattr(kernel, "__name__") == "gaussian":
        # We have a 'shortcut' for Gaussian kernels... this is kinda hacky
        # But maybe worth it given the speedup our shortcut gets us?
        return lambda x, y: 2 - 2*gaussian(x, y, kw.get("sigma", 1))
    else:
        kern = partial(kernel, **kw)
        return lambda x, y: kern(x, x) - 2*kern(x, y) + kern(y, y)