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# scipy.fftpack.rfft

`scipy.fftpack.``rfft`(x, n=None, axis=-1, overwrite_x=False)

  Discrete Fourier transform of a real sequence.

  Parameters: | x : array_like, real-valued The data to transform. n : int, optional Defines the length of the Fourier transform. If n is not specified (the default) then `n = x.shape[axis]`. If `n < x.shape[axis]`, x is truncated, if `n > x.shape[axis]`, x is zero-padded. axis : int, optional The axis along which the transform is applied. The default is the last axis. overwrite_x : bool, optional If set to true, the contents of x can be overwritten. Default is False.
  > Returns: | z : real ndarray The returned real array contains:
  >     [y(0),Re(y(1)),Im(y(1)),...,Re(y(n/2))]              if n is even
  >     [y(0),Re(y(1)),Im(y(1)),...,Re(y(n/2)),Im(y(n/2))]   if n is odd
  > where:
  >     y(j) = sum[k=0..n-1] x[k] * exp(-sqrt(-1)*j*k*2*pi/n)
  >     j = 0..n-1
  Note that `y(-j) == y(n-j).conjugate()`.

  See also

  `fft`, `irfft`, `scipy.fftpack.basic`

  Notes

  Within numerical accuracy, `y == rfft(irfft(y))`.

  Both single and double precision routines are implemented. Half precision inputs will be converted to single precision. Non floating-point inputs will be converted to double precision. Long-double precision inputs are not supported.

  Examples

      >>> from scipy.fftpack import fft, rfft
      >>> a = [9, -9, 1, 3]
      >>> fft(a)
      array([  4. +0.j,   8.+12.j,  16. +0.j,   8.-12.j])
      >>> rfft(a)
      array([  4.,   8.,  12.,  16.])