Accessing Open Data from GWOSC

The Gravitational-Wave Open Science Center

The Gravitational-Wave Open Science Centre (GWOSC) provides strain data from gravitational-wave observatories for public use, including small datasets around each GW event detection, and bulk datasets covering entire observing epochs.

Note

For full details of the available data, please see

https://gwosc.org/data/

TimeSeries.fetch_open_data()

GWpy provides the TimeSeries.fetch_open_data() method as an interface to the GWOSC data archive, requiring users to provide a minimum of information in order to access data.

For example, to fetch 30 seconds of strain data around the first ever gravitational-wave detection (GW150914), you need to give the prefix of the relevant observatory ('H1' for the LIGO Hanford Observatory, 'L1' for LIGO Livingston), and the start and end times of your query. We can use the gwosc Python package to query GWOSC itself for the right central GPS time:

>>> from gwosc.datasets import event_gps
>>> gps = event_gps("GW150914")
>>> start = int(gps) - 15
>>> end = int(gps) + 15

Then we can call TimeSeries.fetch_open_data() to download the calibrated GW strain data in that interval:

>>> from gwpy.timeseries import TimeSeries
>>> data = TimeSeries.fetch_open_data('L1', start, end)

We can then trivially plot these data:

>>> plot = data.plot()
>>> plot.show()

(png)

../../_images/opendata-3.png

Plotting a TimeSeries

For more details on plotting a TimeSeries, see Plotting time-domain data.

Note

TimeSeries.fetch_open_data() keywords

For more details on all of the available keyword options, see the documentation of TimeSeries.fetch_open_data().

Accessing data from Auxiliary Channel Releases

GWOSC has also published a data set containing instrumental sensor data in a three-hour window around GW170814 and throughout the entirety of O3. These data cannot be loaded using TimeSeries.fetch_open_data(), but can be loaded using TimeSeries.get() (or TimeSeriesDict.get()), by specifying host="losc-nds.ligo.org". For more details, see TimeSeries.get().