refactor loss_integrate

[hbaniecki]

change cumsum(c(0, x))[length(x)+1] to sum(x) in all three scenarios

survex/R/metrics.R

Lines 39 to 55 in 64e96d6

	integrated_metric <- cumsum(c(0, tmp))[length(tmp)+1] / (max(times) - min(times))
	return(integrated_metric)
	}
	else if (normalization == "t_max") {
	tmp <- (loss_values[1:(n - 1)] + loss_values[2:n]) * diff(times) / 2
	integrated_metric <- cumsum(c(0, tmp))[length(tmp)+1]
	return(integrated_metric/max(times))
	} else if (normalization == "survival"){
	kaplan_meier <- survfit(y_true~1)
	estimator <- transform_to_stepfunction(kaplan_meier, eval_times = sort(unique(y_true[,1])), type = "survival")
	dwt <- 1 - estimator(times)
	tmp <- (loss_values[1:(n - 1)] + loss_values[2:n]) * diff(dwt) / 2
	integrated_metric <- cumsum(c(0, tmp))[length(tmp)+1]
	return(integrated_metric/(1 - estimator(max(times))))