Time Series data¶

Gravitational-wave detectors are time-domain instruments, recording gravitational-wave amplitude as a differential change in the lengths of each of the interferometer arms. The primary output of these detectors is a single time-stream of gravitational-wave strain (also referred to as h(t)).

Alongside the strain data, thousands of instrumental control and error signals and environmental monitors are recorded in real-time and archived for off-line study. These data are colloquially called the auxiliary channels.

The `TimeSeries`¶

Importing 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:

Creating a TimeSeries 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:

`unit`	The physical unit of these data.
`t0`	X-axis coordinate of the first data point.
`dt`	X-axis sample separation.
`name`	Name for this data set.
`channel`	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:

`TimeSeriesDict`	Ordered key-value mapping of named `TimeSeries` objects.
`TimeSeriesList`	Fancy list representing a list of `TimeSeries`.

Reading/writing time series data¶

Reading and writing time series data
- Automatic discovery of GW detector data
- Built-in file formats

Plotting time series data¶

Plotting time-domain data
- Plotting one TimeSeries
- Plotting multiple TimeSeries together

Reference/API¶

The above documentation references the following objects:

`TimeSeries`	A time-domain data array.
`TimeSeriesDict`	Ordered key-value mapping of named `TimeSeries` objects.
`TimeSeriesList`	Fancy list representing a list of `TimeSeries`.