The Informal Python Bootcamp - Exercise Repository

• emolch (Sebastian)
• karamzad (Nasim)
• Zaccarelli (Riccardo)
• Al-Halbouni (Djamil)
• FelixMSchneider (Felix und Jana)
• nnima (Nima)
• Zakharova (Olya)

• get a github account
• fork this repos (emolch/tipb-exercise) on your github account
• clone the fork on your machine
• add your name to the participants list above
• commit and push the change to your fork on github
• send me a pull request
• wait for your name to appear in emolch/tipb-exercise
• install Pyrocko if you have not done so yet

• the code in randomtrace.py creates and displays a Pyrocko trace with random samples
• try it out
• find documentation of time.time, pyrocko.trace.Trace, and numpy.random.random
• read just enough to understand the code
• try to save this trace in Mini-SEED format with pyrocko.io.save
• why is this not possible? how solve?
• save the trace in text format (using the format='text' option of pyrocko.io.save)
• what are the problems with this text format?
• discuss what would make up a good trace file format
• things to consider: simplicity, platform independence, speed, size, meta information, data corruption, maximum sampling rate, possible time range / span, jump to given time, streamability, meta data, data types, precision

• read documentation on numpy.loadtxt and numpy.savetxt
• commit often while you implement
• start with an empty Python module e.g. yourname_text_trace_io.py
• implement a write function write(trace, filename)
• implement a read function read(filename)
• enhance the read function to allow to only read metadata read(filename, getdata=False)
• write a test function which checks if your read and write functions work properly
• upload your work to github, send a pull request