#!/usr/bin/env python # coding: utf-8 # Gravitational Wave Data Analytics Quickview # =========================================== # # This IPython notebook provides a quick look at short segments of data from the [Gravitational Wave Open Science Center](https://gwosc.org/) # # # * Set the GPS time (t0) and detector in the first cell # * Click "Run All" in the cell menu at the top # * Your plots will appear below # ### SET PARAMETERS: Detector and GPS Time # In[1]: # -- Set a GPS time: t0 = 1126259462.4 # -- GW150914 #-- Choose detector as H1, L1, or V1 detector = 'H1' # We could also try some of these examples times in the H1 detector: # #
# t0 = 1126259462.4 # -- GW150914 # t0 = 1187008882.4 # -- GW170817 # t0 = 933200215 # -- Loud hardware injection # t0 = 1132401286.33 # -- Koi Fish Glitch ## ### Importing Packages # In[2]: import requests, os import matplotlib.pyplot as plt get_ipython().run_line_magic('config', "InlineBackend.figure_format = 'retina'") try: from gwpy.timeseries import TimeSeries except: get_ipython().system(' pip install -q "gwpy==3.0.7"') get_ipython().system(' pip install -q "matplotlib==3.5.3"') get_ipython().system(' pip install -q "astropy==6.0.0"') from gwpy.timeseries import TimeSeries # ### Querying and Downloading Data # # The `gwosc` package provides an interface to querying the open data releases hosted on [Gravitational Wave Open Science Center](https://gwosc.org). Documentations and info of the `gwosc` package can be found in the following links # # - [Documentation](https://gwosc.readthedocs.io/en/latest/) # - [PyPI](https://pypi.org/project/gwosc/) # In[3]: from gwosc.locate import get_urls url = get_urls(detector, t0, t0)[-1] print('Downloading: ' , url) fn = os.path.basename(url) with open(fn,'wb') as strainfile: straindata = requests.get(url) strainfile.write(straindata.content) # ### Plotting the Raw Time-Series Data # In[4]: # -- Read strain data strain = TimeSeries.read(fn,format='hdf5.gwosc') center = int(t0) strain = strain.crop(center-16, center+16) fig1 = strain.plot() plt.show() # ### Plotting the ASD # In[5]: # -- Plot ASD fig2 = strain.asd(fftlength=8).plot() plt.xlim(10,2000) plt.ylim(1e-24, 1e-19) plt.show() # ### Whitening and Band-Passing the Data # In[7]: # -- Whiten and bandpass data white_data = strain.whiten() bp_data = white_data.bandpass(30, 400) fig3 = bp_data.plot() plt.xlim(t0-0.2, t0+0.1) plt.show() # ### Plotting a q-transform of the Data # In[8]: dt = 1 #-- Set width of q-transform plot, in seconds hq = strain.q_transform(outseg=(t0-dt, t0+dt)) fig4 = hq.plot() ax = fig4.gca() ax.grid(False) ax.set_yscale('log') try: fig4.colorbar(label="Normalized energy") except: pass plt.show()