3. Reading Seismograms

Seismograms of various formats (e.g. SAC, MiniSEED, GSE2, SEISAN, Q, etc.) can be imported into a Stream object using the read() function.

Streams are list-like objects which contain multiple Trace objects, i.e. gap-less continuous time series and related header/meta information.

Each Trace object has a attribute called data pointing to a NumPy ndarray of the actual time series and the attribute stats which contains all meta information in a dictionary-like Stats object. Both attributes starttime and endtime of the Stats object are UTCDateTime objects.

The following example demonstrates how a single GSE2-formatted seismogram file is read into a ObsPy Stream object. There exists only one Trace in the given seismogram:

>>> from obspy import read
>>> st = read('http://examples.obspy.org/RJOB_061005_072159.ehz.new')
>>> print(st)
1 Trace(s) in Stream:
.RJOB..Z | 2005-10-06T07:21:59.849998Z - 2005-10-06T07:24:59.844998Z | 200.0 Hz, 36000 samples
>>> len(st)
>>> tr = st[0]  # assign first and only trace to new variable
>>> print(tr)
.RJOB..Z | 2005-10-06T07:21:59.849998Z - 2005-10-06T07:24:59.844998Z | 200.0 Hz, 36000 samples

3.1. Accessing Meta Data

Seismogram meta data, data describing the actual waveform data, are accessed via the stats keyword on each Trace:

>>> print(tr.stats)  
         station: RJOB
         channel: Z
       starttime: 2005-10-06T07:21:59.849998Z
         endtime: 2005-10-06T07:24:59.844998Z
   sampling_rate: 200.0
           delta: 0.005
            npts: 36000
           calib: 0.0948999971151
         _format: GSE2
            gse2: AttribDict({'instype': '      ', 'datatype': 'CM6', 'hang': -1.0, 'auxid': 'RJOB', 'vang': -1.0, 'calper': 1.0})
>>> tr.stats.station
>>> tr.stats.gse2.datatype

3.2. Accessing Waveform Data

The actual waveform data may be retrieved via the data keyword on each Trace:

>>> tr.data
array([-38,  12,  -4, ..., -14,  -3,  -9])
>>> tr.data[0:3]
array([-38,  12,  -4])
>>> len(tr)

3.3. Data Preview

Stream objects offer a plot() method for fast preview of the waveform (requires the obspy.imaging module):

>>> st.plot()

(Source code, png, hires.png)