The FrequencySeries class¶

While gravitational-wave detectors are time-domain instruments, their sensitivity is frequency dependent and so is often measured as a power-spectral-density over the range of interesting gravitational-wave frequencies (~10-10,000 Hz). Additionally, the auxiliary channels used to sense and control instrumental operations each have their own frequency-domain characteristics, contributing to the overall sensitivity spectrum.

The FrequencySeries object is used to represent any frequency series, including the power-spectral (and amplitude-spectral) density series describing instrument performance.

Analogously to the TimeSeries, a new FrequencySeries can be generated from any data sequence along with the minimal f0 and df metadata:

>>> from gwpy.frequencyseries import FrequencySeries
>>> spec = FrequencySeries([1,2,3,4,5,6,7,8,9,10], f0=0, df=1)
>>> print(spec)
FrequencySeries([ 1  2  3  4  5  6  7  8  9 10],
                name: None,
                unit: None,
                epoch: None,
                channel: None,
                f0: 0 Hz,
                df: 1 Hz,
                logf: False)

The full set of metadata that can be provided is as follows:

Generating a FrequencySeries from a TimeSeries¶

The frequency-spectrum of a TimeSeries can be calculated using either of the following methods:

In this example we expand upon plotting a TimeSeries, by calculating the amplitude-spectral density of the gravitational-wave strain data from LHO:

>>> from gwpy.timeseries import TimeSeries
>>> gwdata = TimeSeries.get('H1:LDAS-STRAIN', 'September 16 2010 06:40',
...                         'September 16 2010 06:50')
>>> spectrum = gwdata.asd(8, 4)

where the result is an average spectrum calculated using the Welch method.

Reading/writing frequency-domain data¶

Plotting a FrequencySeries¶

Similary to the TimeSeries, the FrequencySeries object comes with its own plot() method, which will quickly construct a Plot:

>>> plot = spectrum.plot()
>>> ax = plot.gca()
>>> ax.set_xlim(40, 4000)
>>> ax.set_ylabel(r'GW strain ASD [strain$/\sqrt{\mathrm{Hz}}$]')
>>> ax.set_ylim(1e-23, 3e-20)
>>> plot.show()

(png)

FrequencySeries applications¶

FrequencySeries reference¶