sksurv.util.Surv#

class sksurv.util.Surv[source]#

A helper class to create a structured array for survival analysis.

This class provides helper functions to create a structured array that encapsulates the event indicator and the observed time. The resulting structured array is the recommended format for the y argument in scikit-survival’s estimators.

__init__()#

Methods

__init__()

from_arrays(event, time[, name_event, name_time])

Create structured array from event indicator and time arrays.

from_dataframe(event, time, data)

Create structured array from columns in a pandas DataFrame.
static from_arrays(event, time, name_event=None, name_time=None)[source]#

Create structured array from event indicator and time arrays.

Parameters:

  • event (array-like, shape=(n_samples,)) – Event indicator. A boolean array or array with values 0/1, where True or 1 indicates an event and False or 0 indicates right-censoring.

  • time (array-like, shape=(n_samples,)) – Observed time. Time to event or time of censoring.

  • name_event (str, optional, default: 'event') – Name of the event field in the structured array.

  • name_time (str, optional, default: 'time') – Name of the observed time field in the structured array.

Returns:

y – A structured array with two fields. The first field is a boolean where True indicates an event and False indicates right-censoring. The second field is a float with the time of event or time of censoring. The names of the fields are set to the values of name_event and name_time.

Return type:

numpy.ndarray

Examples

>>> from sksurv.util import Surv
>>>
>>> y = Surv.from_arrays(event=[True, False, True],
...                      time=[10, 25, 15])
>>> y
array([( True, 10.), (False, 25.), ( True, 15.)],
    dtype=[('event', '?'), ('time', '<f8')])
>>> y['event']
array([ True, False,  True])
>>> y['time']
array([10., 25., 15.])
static from_dataframe(event, time, data)[source]#

Create structured array from columns in a pandas DataFrame.

Parameters:

  • event (str) – Name of the column in data containing the event indicator. It must be a boolean or have values 0/1, where True or 1 indicates an event and False or 0 indicates right-censoring.

  • time (str) – Name of the column in data containing the observed time (time to event or time of censoring).

  • data (pandas.DataFrame) – A DataFrame with columns for event and time.

Returns:

y – A structured array with two fields. The first field is a boolean where True indicates an event and False indicates right-censoring. The second field is a float with the time of event or time of censoring. The names of the fields are the respective column names.

Return type:

numpy.ndarray

Examples

>>> import pandas as pd
>>> from sksurv.util import Surv
>>>
>>> df = pd.DataFrame({
...     'status': [True, False, True],
...     'followup_time': [10, 25, 15],
... })
>>> y = Surv.from_dataframe(
...     event='status', time='followup_time', data=df,
... )
>>> y
array([( True, 10.), (False, 25.), ( True, 15.)],
    dtype=[('status', '?'), ('followup_time', '<f8')])
>>> y['status']
array([ True, False,  True])
>>> y['followup_time']
array([10., 25., 15.])