Saves and writes ObsPy streams to hdf5 files. Stats attributes are preserved if they are numbers, strings, UTCDateTime objects or numpy arrays. It can be used as a plugin to obspy's read function to read a whole hdf5 file. Alternatively you can iterate over the traces in a hdf5 file with the iterh5 function.
Install h5py and obspy. After that install obspyh5 using pip by:
pip install obspyh5
With conda the package can be installed into a fresh environment with:
conda config --add channels conda-forge conda create -n obsh5 numpy obspy h5py conda activate obsh5 pip install obspyh5
Basic example using the obspy plugin:
>>> from obspy import read >>> stream = read() # load example stream >>> print(stream) ..3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples >>> stream.write('test.h5', 'H5') # declare 'H5' as format >>> print(read('test.h5')) # Order is not preserved! 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples
Example iterating over traces in a huge hdf5 file. After each iteration the trace is not kept in memory and therefore it is possible to process a huge hdf5 file on a PC without problems.
>>> from obspyh5 import iterh5 >>> for trace in iterh5('huge_in.h5') trace.do_something() trace.write('huge_out.h5', 'H5', mode='a') # append mode to write into file
obspyh5 supports alternative indexing.
>>> from obspy import read >>> import obspyh5 >>> print(obspyh5._INDEX) # default index waveforms/{network}.{station}/{location}.{channel}/{starttime.datetime:%Y-%m-%dT%H:%M:%S}_{endtime.datetime:%Y-%m-%dT%H:%M:%S}
The index gets populated by the stats object and the trace number when writing a trace, e.g.
>>> stats = read()[0].stats >>> print(obspyh5._INDEX.format(trc_num=0, **stats)) 'waveforms/BW.RJOB/.EHZ/2009-08-24T00:20:03_2009-08-24T00:20:32'
To change the index use set_index.
>>> obspyh5.set_index('xcorr') # xcorr indexing >>> obspyh5.set_index('waveforms/{network}.{station}/{distance}') # custom indexing >>> obspyh5.set_index('waveforms/{trc_num:03d}_{station}') # use of the trace number
When using the 'xcorr' indexing stats needs the entries 'network1', 'station1', 'location1', 'channel1', 'network2', 'station2', 'location2' and 'channel2' of the first and second station. An example:
>>> from obspy import read >>> import obspyh5 >>> obspyh5.set_index('xcorr') # activate xcorr indexing >>> stream = read() >>> for i, tr in enumerate(stream): # manipulate stats object station1, station2 = 'ST1', 'ST%d' % i channel1, channel2 = 'HHZ', 'HHN' s = tr.stats # we manipulate seed id so that important information gets # printed by obspy s.network, s.station = s.station1, s.channel1 = station1, channel1 s.location, s.channel = s.station2, s.channel2 = station2, channel2 s.network1 = s.network2 = 'BW' s.location1 = s.location2 = '' >>> print(stream) ST1.HHZ.ST0.HHN | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples ST1.HHZ.ST1.HHN | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples ST1.HHZ.ST2.HHN | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples >>> stream.write('test_xcorr.h5', 'H5') >>> print(read('test_xcorr.h5')) ST1.HHZ.ST0.HHN | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples ST1.HHZ.ST1.HHN | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples ST1.HHZ.ST2.HHN | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:32.990000Z | 100.0 Hz, 3000 samples
See also ASDF for a more comprehensive approach.
Use case: Cross-correlation of late Okhotsk coda (notebook).