# Plot waveforms of events on a dates axis

Following a question from my dear colleague Devy, here is how to plot a set of events, occurring at random moments in time. The idea is to plot the waveform of each event with the beginning at the top and the end at the bottom (along the “y” axis) and centred on the origin time…

# North Korean nuclear tests with Obspy

This morning, North Korea tested some nuclear “bomb” somewhere in the middle of the country (confirmed by Pyongyang officials and CTBTO), and many seismic sensors worldwide recorded the triggered waveforms. The location of the test is the same as the 2009 one, confirmed by the location provided by global monitoring networks (USGS, GEOFON). To pythonise…

# New Tutorial Series: Pandas

In the coming months, I’ll prepare some tutorials over an excellent data analysis package called pandas ! To show you the power of pandas, just take a look at this old tutorial, where I exploited the power of itertools to group sparse data into 5 seconds bins. The magic of pandas is that, when you…

# Last Earthquakes tool – ETS powered

While in Indonesia last July, I created a small tool for the Kawah Ijen observers to allow them to search and plot teleseismic events and to calculate theoretical arrival times of the waves at the Ijen stations. It took roughly 2 hours to have a working version of the software, with: a GUI to plot…

# Matplotlib & Datetimes – Tutorial 04: Grouping & Analysing Sparse Data

To extend the previous tutorial (see here), we define a data array that has some information about the event that occurred for each datetime. The plot of data vs time now looks like: The data array is constructed with numpy.random: data = np.random.randint(10000,size=len(times)) Now, we will modify the example from tutorial 03: def group(di): return…