def print_summary(self, decimals=2, **kwargs):
        """
        Print summary statistics describing the fit, the coefficients, and the error bounds.

        Parameters
        -----------
        decimals: int, optional (default=2)
            specify the number of decimal places to show
        kwargs:
            print additional metadata in the output (useful to provide model names, dataset names, etc.) when comparing
            multiple outputs.

        """
        justify = string_justify(18)
        print(self)
        print("{} = {}".format(justify("number of subjects"), self.event_observed.shape[0]))
        print("{} = {}".format(justify("number of events"), np.where(self.event_observed)[0].shape[0]))
        print("{} = {:.{prec}f}".format(justify("log-likelihood"), self._log_likelihood, prec=decimals))
        print(
            "{} = {}".format(
                justify("hypothesis"),
                ", ".join(
                    "%s != %d" % (name, iv) for (name, iv) in zip(self._fitted_parameter_names, self._initial_values)
                ),
            )
        )

        for k, v in kwargs.items():
            print("{} = {}\n".format(justify(k), v))

        print(end="\n")
        print("---")

        df = self.summary
        print(
            df.to_string(
                float_format=format_floats(decimals),
                formatters={"p": format_p_value(decimals), "exp(coef)": format_exp_floats(decimals)},
            )
        )
def print_summary ( self , decimals = 2 , ** kwargs ) : justify = string_justify ( 18 ) print ( self ) print ( "{} = {}" . format ( justify ( "number of subjects" ) , self . event_observed . shape [ 0 ] ) ) print ( "{} = {}" . format ( justify ( "number of events" ) , np . where ( self . event_observed ) [ 0 ] . shape [ 0 ] ) ) print ( "{} = {:.{prec}f}" . format ( justify ( "log-likelihood" ) , self . _log_likelihood , prec = decimals ) ) print ( "{} = {}" . format ( justify ( "hypothesis" ) , ", " . join ( "%s != %d" % ( name , iv ) for ( name , iv ) in zip ( self . _fitted_parameter_names , self . _initial_values ) ) , ) ) for k , v in kwargs . items ( ) : print ( "{} = {}\n" . format ( justify ( k ) , v ) ) print ( end = "\n" ) print ( "---" ) df = self . summary print ( df . to_string ( float_format = format_floats ( decimals ) , formatters = { "p" : format_p_value ( decimals ) , "exp(coef)" : format_exp_floats ( decimals ) } , ) )
Print summary statistics describing the fit, the coefficients, and the error bounds.

        Parameters
        -----------
        decimals: int, optional (default=2)
            specify the number of decimal places to show
        kwargs:
            print additional metadata in the output (useful to provide model names, dataset names, etc.) when comparing
            multiple outputs.