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# scipy.special.diric

`scipy.special.``diric`(x, n)

  Periodic sinc function, also called the Dirichlet function.

  The Dirichlet function is defined as:

      diric(x) = sin(x * n/2) / (n * sin(x / 2)),

  where n is a positive integer.

  Parameters: | x : array_like Input data n : int Integer defining the periodicity.
  Returns: | diric : ndarray

  Examples

      >>> from scipy import special
      >>> import matplotlib.pyplot as plt

      >>> x = np.linspace(-8*np.pi, 8*np.pi, num=201)
      >>> plt.figure(figsize=(8, 8));
      >>> for idx, n in enumerate([2, 3, 4, 9]):
      ...     plt.subplot(2, 2, idx+1)
      ...     plt.plot(x, special.diric(x, n))
      ...     plt.title('diric, n={}'.format(n))
      >>> plt.show()

  (Source code)

  The following example demonstrates that `diric` gives the magnitudes (modulo the sign and scaling) of the Fourier coefficients of a rectangular pulse.

  Suppress output of values that are effectively 0:

      >>> np.set_printoptions(suppress=True)

  Create a signal x of length m with k ones:

      >>> m = 8
      >>> k = 3
      >>> x = np.zeros(m)
      >>> x[:k] = 1

  Use the FFT to compute the Fourier transform of x, and inspect the magnitudes of the coefficients:

      >>> np.abs(np.fft.fft(x))
      array([ 3.        ,  2.41421356,  1.        ,  0.41421356,  1.        ,
              0.41421356,  1.        ,  2.41421356])

  Now find the same values (up to sign) using `diric`. We multiply by k to account for the different scaling conventions of `numpy.fft.fft` and `diric`:

      >>> theta = np.linspace(0, 2*np.pi, m, endpoint=False)
      >>> k * special.diric(theta, k)
      array([ 3.        ,  2.41421356,  1.        , -0.41421356, -1.        ,
             -0.41421356,  1.        ,  2.41421356])