Time Series data¶
Gravitationalwave detectors are timedomain instruments, recording gravitationalwave amplitude as a differential change in the lengths of each of the interferometer arms. The primary output of these detectors is a single timestream of gravitationalwave strain (also referred to as h(t)).
Alongside the strain data, thousands of instrumental control and error signals and environmental monitors are recorded in realtime and archived for offline study. These data are colloquially called the auxiliary channels.
The TimeSeries
¶
from gwpy.timeseries import TimeSeries
GWpy provides the TimeSeries
object as a way of representing time series
data.
The TimeSeries
is built on top of the numpy.ndarray
, and so many
methods and applications of this object should be familiar to
numpy
users.
For example, to create a simple TimeSeries
filled with
random
data:
>>> from numpy.random import random
>>> from gwpy.timeseries import TimeSeries
>>> t = TimeSeries(random(1000))
>>> print(t)
TimeSeries([ 0.59442285, 0.61979421, 0.62968915,..., 0.98309223,
0.94513298, 0.1826175 ]
unit: Unit(dimensionless),
t0: 0.0 s,
dt: 1.0 s,
name: None,
channel: None)
Here we see the random data we have created, as well as the associated metadata common to any time series data:
The physical unit of these data 

Xaxis coordinate of the first data point 

Xaxis sample separation 

Name for this data set 

Instrumental channel associated with these data 
Associated classes¶
Alongside the TimeSeries
class, gwpy.timeseries
module provides a
small set of related classes for handling collections of data:
Ordered keyvalue mapping of named 

Fancy list representing a list of 
Reading/writing time series data¶
Plotting time series data¶
Reference/API¶
The above documentation references the following objects:
A timedomain data array. 

Ordered keyvalue mapping of named 

Fancy list representing a list of 