original_docstring: r"""
  
          Calculates the mean of the Gamma distribution with given parameters.
  
          .. math::
              E = \frac{\alpha}{\beta}
  
          Parameters
          ----------
  
          alpha : numpy array or scalar
              The shape parameter for the Gamma distribution
          beta : numpy array or scalar
              The scale parameter for the Gamma distribution
  
          Returns
          -------
  
          mean : scalar or numpy array
              The mean(s) of the Gamma distribution
  
          Examples
          --------
          >>> from surpyval import Gamma
          >>> Gamma.mean(3, 4)
          0.75
          
docstring: r"""
  Calculates the mean of the Gamma distribution with given parameters.
  
  
  
  Parameters
  
  alpha : numpy array or scalar
  The shape parameter for the Gamma distribution
  beta : numpy array or scalar
  The scale parameter for the Gamma distribution
  
  Returns
  
  mean : scalar or numpy array
  The mean(s) of the Gamma distribution
  
  Examples
  
  
docstring_tokens: r " " " Calculates the mean of the Gamma distribution with given parameters . Parameters alpha : numpy array or scalar The shape parameter for the Gamma distribution beta : numpy array or scalar The scale parameter for the Gamma distribution Returns mean : scalar or numpy array The mean ( s ) of the Gamma distribution Examples
code: def mean(self, alpha, beta):
          r"""
  
          Calculates the mean of the Gamma distribution with given parameters.
  
          .. math::
              E = \frac{\alpha}{\beta}
  
          Parameters
          ----------
  
          alpha : numpy array or scalar
              The shape parameter for the Gamma distribution
          beta : numpy array or scalar
              The scale parameter for the Gamma distribution
  
          Returns
          -------
  
          mean : scalar or numpy array
              The mean(s) of the Gamma distribution
  
          Examples
          --------
          >>> from surpyval import Gamma
          >>> Gamma.mean(3, 4)
          0.75
          """
          return alpha / beta
code_tokens: def mean ( self , alpha , beta ) : return alpha / beta
short_docstring: r"""
  Calculates the mean of the Gamma distribution with given parameters.
short_docstring_tokens: r " " " Calculates the mean of the Gamma distribution with given parameters .
comment: r"""
  
          Calculates the mean of the Gamma distribution with given parameters.
  
          .. math::
              E = \frac{\alpha}{\beta}
  
          Parameters
          ----------
  
          alpha : numpy array or scalar
              The shape parameter for the Gamma distribution
          beta : numpy array or scalar
              The scale parameter for the Gamma distribution
  
          Returns
          -------
  
          mean : scalar or numpy array
              The mean(s) of the Gamma distribution
  
          Examples
          --------
          >>> from surpyval import Gamma
          >>> Gamma.mean(3, 4)
          0.75
          """