docs: def quantile_gaussianize(x):
      """Normalize a sequence of values via rank and Normal c.d.f.
  
      Args:
          x (array_like): sequence of values.
  
      Returns:
          Gaussian-normalized values.
  
      Example:
  
      .. doctest::
  
          >>> from scipy_sugar.stats import quantile_gaussianize
          >>> print(quantile_gaussianize([-1, 0, 2]))
          [-0.67448975  0.          0.67448975]
      """
      from scipy.stats import norm, rankdata
  
      x = asarray(x, float).copy()
      ok = isfinite(x)
      x[ok] *= -1
      y = empty_like(x)
      y[ok] = rankdata(x[ok])
      y[ok] = norm.isf(y[ok] / (sum(ok) + 1))
      y[~ok] = x[~ok]
      return y