parameters: (self, x, *args, **kwds)
return_statement: return output
docstring: Log of the cumulative distribution function at x of the given RV.
  
          Parameters
          ----------
          x : array_like
              quantiles
          arg1, arg2, arg3,... : array_like
              The shape parameter(s) for the distribution (see docstring of the
              instance object for more information)
          loc : array_like, optional
              location parameter (default=0)
          scale : array_like, optional
              scale parameter (default=1)
  
          Returns
          -------
          logcdf : array_like
              Log of the cumulative distribution function evaluated at x
docstring_summary: Log of the cumulative distribution function at x of the given RV.
docstring_tokens: Log of the cumulative distribution function at x of the given RV .
function: def logcdf(self, x, *args, **kwds):
          """
          Log of the cumulative distribution function at x of the given RV.
  
          Parameters
          ----------
          x : array_like
              quantiles
          arg1, arg2, arg3,... : array_like
              The shape parameter(s) for the distribution (see docstring of the
              instance object for more information)
          loc : array_like, optional
              location parameter (default=0)
          scale : array_like, optional
              scale parameter (default=1)
  
          Returns
          -------
          logcdf : array_like
              Log of the cumulative distribution function evaluated at x
  
          """
          args, loc, scale = self._parse_args(*args, **kwds)
          x, loc, scale = map(asarray, (x, loc, scale))
          args = tuple(map(asarray, args))
          dtyp = np.find_common_type([x.dtype, np.float64], [])
          x = np.asarray((x - loc)/scale, dtype=dtyp)
          cond0 = self._argcheck(*args) & (scale > 0)
          cond1 = self._open_support_mask(x) & (scale > 0)
          cond2 = (x >= self.b) & cond0
          cond = cond0 & cond1
          output = empty(shape(cond), dtyp)
          output.fill(NINF)
          place(output, (1-cond0)*(cond1 == cond1)+np.isnan(x), self.badvalue)
          place(output, cond2, 0.0)
          if np.any(cond):  # call only if at least 1 entry
              goodargs = argsreduce(cond, *((x,)+args))
              place(output, cond, self._logcdf(*goodargs))
          if output.ndim == 0:
              return output[()]
          return output
function_tokens: def logcdf ( self , x , * args , * * kwds ) : args , loc , scale = self . _parse_args ( * args , * * kwds ) x , loc , scale = map ( asarray , ( x , loc , scale ) ) args = tuple ( map ( asarray , args ) ) dtyp = np . find_common_type ( [ x . dtype , np . float64 ] , [ ] ) x = np . asarray ( ( x - loc ) / scale , dtype = dtyp ) cond0 = self . _argcheck ( * args ) & ( scale > 0 ) cond1 = self . _open_support_mask ( x ) & ( scale > 0 ) cond2 = ( x >= self . b ) & cond0 cond = cond0 & cond1 output = empty ( shape ( cond ) , dtyp ) output . fill ( NINF ) place ( output , ( 1 - cond0 ) * ( cond1 == cond1 ) + np . isnan ( x ) , self . badvalue ) place ( output , cond2 , 0.0 ) if np . any ( cond ) : # call only if at least 1 entry goodargs = argsreduce ( cond , * ( ( x , ) + args ) ) place ( output , cond , self . _logcdf ( * goodargs ) ) if output . ndim == 0 : return output [ ( ) ] return output