ObsPy Tutorial¶

This tutorial does not attempt to be comprehensive and cover every single feature. Instead, it introduces many of ObsPy’s most noteworthy features, and will give you a good idea of the library’s flavor and style.

A pdf version of the Tutorial is available here.

There are also IPython notebooks available online with an introduction to Python (with solutions/output) and an introduction to ObsPy (with solutions/output).

Introduction to ObsPy¶

1. Python Introduction for Seismologists
2. UTCDateTime
- 2.1. Initialization
- 2.2. Attribute Access
- 2.3. Handling time differences
- 2.4. Exercises
3. Reading Seismograms
- 3.1. Accessing Meta Data
- 3.2. Accessing Waveform Data
- 3.3. Data Preview
4. Waveform Plotting Tutorial
- 4.1. Basic Plotting
- 4.2. Customized Plots
- 4.3. Saving Plot to File
- 4.4. Plotting multiple Channels
- 4.5. Creating a One-Day Plot
- 4.6. Plotting a Record Section
- 4.7. Plot & Color Options
5. Retrieving Data from Data Centers
- 5.1. ArcLink Protocol
- 5.2. IRIS Web Services
- 5.3. Earthworm Wave Server
- 5.4. NERIES Web Services
6. Filtering Seismograms
7. Downsampling Seismograms
8. Merging Seismograms
9. Beamforming - FK Analysis
10. Seismogram Envelopes
11. Plotting Spectrograms
12. Trigger/Picker Tutorial
- 12.1. Reading Waveform Data
- 12.2. Available Methods
- 12.3. Trigger Examples
- 12.4. Network Coincidence Trigger Example
- 12.5. Advanced Network Coincidence Trigger Example with Similarity Detection
- 12.6. Picker Examples
- 12.7. Advanced Example
13. Poles and Zeros, Frequency Response
14. Seismometer Correction/Simulation
- 14.1. Using a PAZ dictionary
- 14.2. Calculating response from filter stages using evalresp..
15. Clone an Existing Dataless SEED File
16. Export Seismograms to MATLAB
17. Export Seismograms to ASCII
- 17.1. Built-in Formats
- 17.2. Custom Format
18. Anything to MiniSEED
19. Beachball Plot
20. Basemap Plot with Beachballs
- 20.1. Basemap Plot of a Local Area
- 20.2. Basemap Plot of the Globe
21. Interfacing R from Python
22. Coordinate Conversions
23. Hierarchical Clustering
24. Visualizing Probabilistic Power Spectral Densities
25. Array Response Function
26. Continuous Wavelet Transform
- 26.1. Using ObsPy
- 26.2. Using MLPY
27. Time Frequency Misfit
- 27.1. Plot the Time Frequency Representation
- 27.2. Plot the Time Frequency Misfits
- 27.3. Plot the Time Frequency Goodness-Of-Fit
- 27.4. Multi Component Data
- 27.5. Local normalization
28. Visualize Data Availability of Local Waveform Archive
29. Travel Time Plot
30. Cross Correlation Pick Correction
31. Handling custom defined tags in QuakeML and the ObsPy Catalog/Event framework
32. Connecting to a SeedLink Server
- 32.1. Ok

Advanced Exercise¶

In the advanced exercise we show how ObsPy can be used to develop an automated processing workflow. We start out with very simple tasks and then automate the routine step by step. For all exercises solutions are provided.

Advanced Exercise