plot_survival

plot_survival(
    time
    survival
    *
    censored=None
    lower=None
    upper=None
    label=None
    ax=None
    show_censors=True
    ci_alpha=0.25
    **kwargs
)

Draw a Kaplan-Meier curve and read it as a survival layer.

The curve is drawn as ax.step(time, survival, where="post") draws it, with the band as a shaded step and each censoring time as a tick on the curve. Several calls on one axes draw the arms of one chart, which a reader moves between with Up and Down.

Parameters

Name	Type	Description	Default
time	array_like	The times at which the estimate is stated, strictly increasing, usually starting at 0. The estimate holds from each time until the next.	required
survival	array_like	The survival probability from each time on.	required
censored	iterable of float	The times at which a subject left the study without the event happening. The curve does not step there; each is announced as censored, and the reader can move between them with the rotor.	None
lower	array_like	The confidence band at each time, announced after the estimate.	None
upper	array_like	The confidence band at each time, announced after the estimate.	None
label	str	The arm’s name, in the legend and in what is announced.	None
ax	Axes	Where to draw; the current axes by default.	None
show_censors	bool	Whether to draw the censoring ticks. They are announced either way.	True
ci_alpha	float	The band’s opacity.	0.25
**kwargs	Any	Passed to ax.plot for the curve, such as color.	{}

Returns

Name	Type	Description
	Axes	The axes drawn on.

Raises

Name	Type	Description
	ValueError	As :func:survival_points raises.

Notes

survival is an experimental type; see docs/stability.qmd.

Examples

>>> import matplotlib.pyplot as plt
>>> import maidr
>>> fig, ax = plt.subplots()
>>> maidr.plot_survival(
...     [0, 3, 6, 9], [1.0, 0.88, 0.71, 0.5], censored=[7], label="Control", ax=ax
... )
>>> maidr.show(fig)