Cumulative plot with show_censors option

When I use KaplanMeierFitter.plot_cumulative_density with show_censors=True, I got AttributeError: ‘PlotEstimateConfig’ object has no attribute ‘predict_at_times’.

I modified the end of plotting.py from

        else:
            self.estimate_ = estimate
            self.confidence_interval_ = kwargs.pop("confidence_intervals")

to

        else:
            self.estimate_ = estimate
            self.confidence_interval_ = kwargs.pop("confidence_intervals")
            self.predict_at_times = cls.cumulative_density_at_times

I successfully got my cumulative plot. But I think the code should be changed more correct way.

[tsjshg]

Hi Cameron, your solution fixed the error in version 0.23.9. I really appreciate your prompt response, and giving us this great library for lifetime data analysis!

[CamDavidsonPilon]

@tsjshg a better solution, and the one I’ll implement, is to change the following:

from lifelines.plotting import _plot_estimate  
       
def plot_cumulative_density(self, **kwargs):
    return _plot_estimate(
        self,
        estimate="cumulative_density_",
        **kwargs
    )

KaplanMeierFitter.plot_cumulative_density = plot_cumulative_density

So your entire script becomes:

import lifelines
from lifelines.datasets import load_canadian_senators
data = load_canadian_senators()

from lifelines.plotting import _plot_estimate  
       
def plot_cumulative_density(self, **kwargs):
    return _plot_estimate(
        self,
        estimate="cumulative_density_",
        **kwargs
    )

KaplanMeierFitter.plot_cumulative_density = plot_cumulative_density

kmf = KaplanMeierFitter()
kmf.fit(data['diff_days'], data['observed'])
kmf.plot_cumulative_density(show_censors=True)