parameters: (self)
docstring: Returns the minimum representable value in this data type.
  
      Raises:
        TypeError: if this is a non-numeric, unordered, or quantized type.
docstring_summary: Returns the minimum representable value in this data type.
docstring_tokens: Returns the minimum representable value in this data type .
function: def min(self):
      """Returns the minimum representable value in this data type.
  
      Raises:
        TypeError: if this is a non-numeric, unordered, or quantized type.
  
      """
      if (self.is_quantized or self.base_dtype in
          (bool, string, complex64, complex128)):
        raise TypeError("Cannot find minimum value of %s." % self)
  
      # there is no simple way to get the min value of a dtype, we have to check
      # float and int types separately
      try:
        return np.finfo(self.as_numpy_dtype()).min
      except:  # bare except as possible raises by finfo not documented
        try:
          return np.iinfo(self.as_numpy_dtype()).min
        except:
          raise TypeError("Cannot find minimum value of %s." % self)
function_tokens: def min ( self ) : if ( self . is_quantized or self . base_dtype in ( bool , string , complex64 , complex128 ) ) : raise TypeError ( "Cannot find minimum value of %s." % self ) # there is no simple way to get the min value of a dtype, we have to check # float and int types separately try : return np . finfo ( self . as_numpy_dtype ( ) ) . min except : # bare except as possible raises by finfo not documented try : return np . iinfo ( self . as_numpy_dtype ( ) ) . min except : raise TypeError ( "Cannot find minimum value of %s." % self )