# extract_time()


Extract the times from an event-time vector.


Usage

``` python
extract_time(x)
```


The shape depends on the data: a 1-D array when no element is interval-censored, otherwise a 2-D array with columns `time` and `time_max`, where `time_max` is missing (`nan`) for elements that aren't interval-censored.


## Parameters


`x: Any`  
An [EventTime](EventTime.md#greenwood.EventTime) vector.


## Returns


`numpy.ndarray`  
A 1-D float array of times, or a 2-D float array of shape `(n, 2)` holding `time` and `time_max` when any element is interval-censored.


## Examples


``` python
import greenwood as gw

x = gw.event_time(time=[7, 5, 2], status=["e", "r", "i"], time_max=[None, None, 4])
gw.extract_time(x)
```


    array([[ 7., nan],
           [ 5., nan],
           [ 2.,  4.]])


Without intervals, the result is 1-D:


``` python
gw.extract_time(x[0:2])
```


    array([7., 5.])