class_docstr: The Output class stores the output of an ODR run.
  
  Attributes
  ----------
  beta : ndarray
      Estimated parameter values, of shape (q,).
  sd_beta : ndarray
      Standard deviations of the estimated parameters, of shape (p,).
  cov_beta : ndarray
      Covariance matrix of the estimated parameters, of shape (p,p).
      Note that this `cov_beta` is not scaled by the residual variance 
      `res_var`, whereas `sd_beta` is. This means 
      ``np.sqrt(np.diag(output.cov_beta * output.res_var))`` is the same 
      result as `output.sd_beta`.
  delta : ndarray, optional
      Array of estimated errors in input variables, of same shape as `x`.
  eps : ndarray, optional
      Array of estimated errors in response variables, of same shape as `y`.
  xplus : ndarray, optional
      Array of ``x + delta``.
  y : ndarray, optional
      Array ``y = fcn(x + delta)``.
  res_var : float, optional
      Residual variance.
  sum_square : float, optional
      Sum of squares error.
  sum_square_delta : float, optional
      Sum of squares of delta error.
  sum_square_eps : float, optional
      Sum of squares of eps error.
  inv_condnum : float, optional
      Inverse condition number (cf. ODRPACK UG p. 77).
  rel_error : float, optional
      Relative error in function values computed within fcn.
  work : ndarray, optional
      Final work array.
  work_ind : dict, optional
      Indices into work for drawing out values (cf. ODRPACK UG p. 83).
  info : int, optional
      Reason for returning, as output by ODRPACK (cf. ODRPACK UG p. 38).
  stopreason : list of str, optional
      `info` interpreted into English.
  
  Notes
  -----
  Takes one argument for initialization, the return value from the
  function `~scipy.odr.odr`. The attributes listed as "optional" above are
  only present if `~scipy.odr.odr` was run with ``full_output=1``.
code: def __init__(self, output):
      self.beta = output[0]
      self.sd_beta = output[1]
      self.cov_beta = output[2]
  
      if len(output) == 4:
          # full output
          self.__dict__.update(output[3])
          self.stopreason = _report_error(self.info)
  
imports: import os
  import numpy
  from warnings import warn
  from scipy.odr import __odrpack
label_desc: Use image node_id 1 to create a new Output object  with example: obj = Output(output)