parameters: (self, x, df, scale)
return_statement: return np.exp(self.logpdf(x, df, scale))
docstring: Wishart probability density function.
  
          Parameters
          ----------
          x : array_like
              Quantiles, with the last axis of `x` denoting the components.
              Each quantile must be a symmetric positive definite matrix.
          %(_doc_default_callparams)s
  
          Returns
          -------
          pdf : ndarray
              Probability density function evaluated at `x`
  
          Notes
          -----
          %(_doc_callparams_note)s
docstring_summary: Wishart probability density function.
docstring_tokens: Wishart probability density function .
function: def pdf(self, x, df, scale):
          """
          Wishart probability density function.
  
          Parameters
          ----------
          x : array_like
              Quantiles, with the last axis of `x` denoting the components.
              Each quantile must be a symmetric positive definite matrix.
          %(_doc_default_callparams)s
  
          Returns
          -------
          pdf : ndarray
              Probability density function evaluated at `x`
  
          Notes
          -----
          %(_doc_callparams_note)s
  
          """
          return np.exp(self.logpdf(x, df, scale))
function_tokens: def pdf ( self , x , df , scale ) : return np . exp ( self . logpdf ( x , df , scale ) )