parameters: (n, mu=False)
return_statement: return ((xw[0] + 1) / 2,) + xw[1:]
docstring: r"""Gauss-Chebyshev (first kind, shifted) quadrature.
  
      Computes the sample points and weights for Gauss-Chebyshev quadrature.
      The sample points are the roots of the n-th degree shifted Chebyshev
      polynomial of the first kind, :math:`T_n(x)`.  These sample points and
      weights correctly integrate polynomials of degree :math:`2n - 1` or less
      over the interval :math:`[0, 1]` with weight function
      :math:`f(x) = 1/\sqrt{x - x^2}`.
  
      Parameters
      ----------
      n : int
          quadrature order
      mu : bool, optional
          If True, return the sum of the weights, optional.
  
      Returns
      -------
      x : ndarray
          Sample points
      w : ndarray
          Weights
      mu : float
          Sum of the weights
  
      See Also
      --------
      scipy.integrate.quadrature
      scipy.integrate.fixed_quad
docstring_summary: r"""Gauss-Chebyshev (first kind, shifted) quadrature.
docstring_tokens: r Gauss - Chebyshev ( first kind shifted ) quadrature .
function: def roots_sh_chebyt(n, mu=False):
      r"""Gauss-Chebyshev (first kind, shifted) quadrature.
  
      Computes the sample points and weights for Gauss-Chebyshev quadrature.
      The sample points are the roots of the n-th degree shifted Chebyshev
      polynomial of the first kind, :math:`T_n(x)`.  These sample points and
      weights correctly integrate polynomials of degree :math:`2n - 1` or less
      over the interval :math:`[0, 1]` with weight function
      :math:`f(x) = 1/\sqrt{x - x^2}`.
  
      Parameters
      ----------
      n : int
          quadrature order
      mu : bool, optional
          If True, return the sum of the weights, optional.
  
      Returns
      -------
      x : ndarray
          Sample points
      w : ndarray
          Weights
      mu : float
          Sum of the weights
  
      See Also
      --------
      scipy.integrate.quadrature
      scipy.integrate.fixed_quad
      """
      xw = roots_chebyt(n, mu)
      return ((xw[0] + 1) / 2,) + xw[1:]
function_tokens: def roots_sh_chebyt ( n , mu = False ) : xw = roots_chebyt ( n , mu ) return ( ( xw [ 0 ] + 1 ) / 2 , ) + xw [ 1 : ]