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# scipy.linalg.dft

`scipy.linalg.``dft`(n, scale=None)

  Discrete Fourier transform matrix.

  Create the matrix that computes the discrete Fourier transform of a sequence [R96]. The n-th primitive root of unity used to generate the matrix is exp(-2*pi*i/n), where i = sqrt(-1).

  Parameters: | n : int Size the matrix to create. scale : str, optional Must be None, ‘sqrtn’, or ‘n’. If scale is ‘sqrtn’, the matrix is divided by sqrt(n). If scale is ‘n’, the matrix is divided by n. If scale is None (the default), the matrix is not normalized, and the return value is simply the Vandermonde matrix of the roots of unity.
  Returns: | m : (n, n) ndarray The DFT matrix.

  Notes

  When scale is None, multiplying a vector by the matrix returned by `dft` is mathematically equivalent to (but much less efficient than) the calculation performed by `scipy.fftpack.fft`.

  New in version 0.14.0.

  References

  [R96] | (1, 2) “DFT matrix”, http://en.wikipedia.org/wiki/DFT_matrix

  Examples

      >>> from scipy.linalg import dft
      >>> np.set_printoptions(precision=5, suppress=True)
      >>> x = np.array([1, 2, 3, 0, 3, 2, 1, 0])
      >>> m = dft(8)
      >>> m.dot(x)   # Compute the DFT of x
      array([ 12.+0.j,  -2.-2.j,   0.-4.j,  -2.+2.j,   4.+0.j,  -2.-2.j,
              -0.+4.j,  -2.+2.j])

  Verify that `m.dot(x)` is the same as `fft(x)`.

      >>> from scipy.fftpack import fft
      >>> fft(x)     # Same result as m.dot(x)
      array([ 12.+0.j,  -2.-2.j,   0.-4.j,  -2.+2.j,   4.+0.j,  -2.-2.j,
               0.+4.j,  -2.+2.j])