temporian.EventSet.moving_sum #
moving_sum(
window_length: WindowLength,
sampling: Optional[EventSetOrNode] = None,
) -> EventSetOrNode
Computes the sum of values in a sliding window over an
EventSet
.
For each t in sampling, and for each feature independently, returns at time t the sum of values for the feature in the window (t - window_length, t].
sampling
can't be specified if a variable window_length
is
specified (i.e. if window_length
is an EventSet).
If sampling
is specified or window_length
is an EventSet, the moving
window is sampled at each timestamp in them, else it is sampled on the
input's.
Missing values (such as NaNs) are ignored.
If the window does not contain any values (e.g., all the values are missing, or the window does not contain any sampling), outputs missing values.
Example
>>> a = tp.event_set(
... timestamps=[0, 1, 2, 5, 6, 7],
... features={"value": [np.nan, 1, 5, 10, 15, 20]},
... )
>>> b = a.moving_sum(tp.duration.seconds(4))
>>> b
indexes: ...
(6 events):
timestamps: [0. 1. 2. 5. 6. 7.]
'value': [ 0. 1. 6. 15. 25. 45.]
...
See EventSet.moving_count()
for
examples of moving window operations with external sampling and indices.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
window_length |
WindowLength
|
Sliding window's length. |
required |
sampling |
Optional[EventSetOrNode]
|
Timestamps to sample the sliding window's value at. If not provided, timestamps in the input are used. |
None
|
Returns:
Type | Description |
---|---|
EventSetOrNode
|
EventSet containing the moving sum of each feature in the input. |