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# scipy.fftpack.convolve.init_convolution_kernel

`scipy.fftpack.convolve.``init_convolution_kernel` = <fortran object>
  init_convolution_kernel - Function signature:
    omega = init_convolution_kernel(n,kernel_func,[d,zero_nyquist,kernel_func_extra_args])
  Required arguments:
    n : input int kernel_func : call-back function
  Optional arguments:
    d := 0 input int kernel_func_extra_args := () input tuple zero_nyquist := d%2 input int
  Return objects:
    omega : rank-1 array(‘d’) with bounds (n)
  Call-back functions:

    def kernel_func(k): return kernel_func Required arguments:

    > k : input int

    Return objects:
      kernel_func : float

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