Source code for obspy.core.stream

# -*- coding: utf-8 -*-
"""
Module for handling ObsPy Stream objects.

:copyright:
    The ObsPy Development Team (devs@obspy.org)
:license:
    GNU Lesser General Public License, Version 3
    (https://www.gnu.org/copyleft/lesser.html)
"""
from __future__ import (absolute_import, division, print_function,
                        unicode_literals)
from future.builtins import *  # NOQA
from future.utils import native_str

import copy
import fnmatch
import math
import os
import pickle
import warnings
from glob import glob, has_magic

from pkg_resources import load_entry_point
import numpy as np

from obspy.core import compatibility
from obspy.core.trace import Trace
from obspy.core.utcdatetime import UTCDateTime
from obspy.core.util import NamedTemporaryFile
from obspy.core.util.base import (ENTRY_POINTS, _get_function_from_entry_point,
                                  _read_from_plugin, download_to_file)
from obspy.core.util.decorator import (deprecated, map_example_filename,
                                       raise_if_masked, uncompress_file)
from obspy.core.util.misc import get_window_times


_headonly_warning_msg = (
    "Keyword headonly cannot be combined with starttime, endtime or dtype.")


@map_example_filename("pathname_or_url")
[docs]def read(pathname_or_url=None, format=None, headonly=False, starttime=None, endtime=None, nearest_sample=True, dtype=None, apply_calib=False, **kwargs): """ Read waveform files into an ObsPy Stream object. The :func:`~obspy.core.stream.read` function opens either one or multiple waveform files given via file name or URL using the ``pathname_or_url`` attribute. The format of the waveform file will be automatically detected if not given. See the `Supported Formats`_ section below for available formats. This function returns an ObsPy :class:`~obspy.core.stream.Stream` object, a ``list``-like object of multiple ObsPy :class:`~obspy.core.trace.Trace` objects. :type pathname_or_url: str or io.BytesIO, optional :param pathname_or_url: String containing a file name or a URL or a open file-like object. Wildcards are allowed for a file name. If this attribute is omitted, an example :class:`~obspy.core.stream.Stream` object will be returned. :type format: str, optional :param format: Format of the file to read (e.g. ``"MSEED"``). See the `Supported Formats`_ section below for a list of supported formats. If format is set to ``None`` it will be automatically detected which results in a slightly slower reading. If a format is specified, no further format checking is done. :type headonly: bool, optional :param headonly: If set to ``True``, read only the data header. This is most useful for scanning available meta information of huge data sets. :type starttime: :class:`~obspy.core.utcdatetime.UTCDateTime`, optional :param starttime: Specify the start time to read. :type endtime: :class:`~obspy.core.utcdatetime.UTCDateTime`, optional :param endtime: Specify the end time to read. :type nearest_sample: bool, optional :param nearest_sample: Only applied if `starttime` or `endtime` is given. Select nearest sample or the one containing the specified time. For more info, see :meth:`~obspy.core.trace.Trace.trim`. :type dtype: :class:`numpy.dtype`, optional :param dtype: Convert data of all traces into given numpy.dtype. :type apply_calib: bool, optional :param apply_calib: Automatically applies the calibration factor ``trace.stats.calib`` for each trace, if set. Defaults to ``False``. :param kwargs: Additional keyword arguments passed to the underlying waveform reader method. :return: An ObsPy :class:`~obspy.core.stream.Stream` object. .. rubric:: Basic Usage In most cases a filename is specified as the only argument to :func:`~obspy.core.stream.read`. For a quick start you may omit all arguments and ObsPy will create and return a basic example seismogram. Further usages of the :func:`~obspy.core.stream.read` function can be seen in the `Further Examples`_ section underneath. >>> from obspy import read >>> st = read() >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z - ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z - ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z - ... | 100.0 Hz, 3000 samples .. rubric:: _`Supported Formats` Additional ObsPy modules extend the functionality of the :func:`~obspy.core.stream.read` function. The following table summarizes all known file formats currently supported by ObsPy. The table order also reflects the order of the autodetection routine if no format option is specified. Please refer to the `Linked Function Call`_ of each module for any extra options available at the import stage. %s Next to the :func:`~obspy.core.stream.read` function the :meth:`~obspy.core.stream.Stream.write` method of the returned :class:`~obspy.core.stream.Stream` object can be used to export the data to the file system. .. rubric:: _`Further Examples` Example waveform files may be retrieved via https://examples.obspy.org. (1) Reading multiple local files using wildcards. The following code uses wildcards, in this case it matches two files. Both files are then read into a single :class:`~obspy.core.stream.Stream` object. >>> from obspy import read # doctest: +SKIP >>> st = read("/path/to/loc_R*.z") # doctest: +SKIP >>> print(st) # doctest: +SKIP 2 Trace(s) in Stream: .RJOB..Z | 2005-08-31T02:33:49.850000Z - ... | 200.0 Hz, 12000 samples .RNON..Z | 2004-06-09T20:05:59.850000Z - ... | 200.0 Hz, 12000 samples (2) Reading a local file without format detection. Using the ``format`` parameter disables the automatic detection and enforces reading a file in a given format. >>> from obspy import read >>> st = read("/path/to/loc_RJOB20050831023349.z", format="GSE2") >>> print(st) # doctest: +ELLIPSIS 1 Trace(s) in Stream: .RJOB..Z | 2005-08-31T02:33:49.850000Z - ... | 200.0 Hz, 12000 samples (3) Reading a remote file via HTTP protocol. >>> from obspy import read >>> st = read("https://examples.obspy.org/loc_RJOB20050831023349.z") >>> print(st) # doctest: +ELLIPSIS 1 Trace(s) in Stream: .RJOB..Z | 2005-08-31T02:33:49.850000Z - ... | 200.0 Hz, 12000 samples (4) Reading a compressed files. >>> from obspy import read >>> st = read("/path/to/tspair.ascii.gz") >>> print(st) # doctest: +ELLIPSIS 1 Trace(s) in Stream: XX.TEST..BHZ | 2008-01-15T00:00:00.025000Z - ... | 40.0 Hz, 635 samples >>> st = read("https://examples.obspy.org/slist.ascii.bz2") >>> print(st) # doctest: +ELLIPSIS 1 Trace(s) in Stream: XX.TEST..BHZ | 2008-01-15T00:00:00.025000Z - ... | 40.0 Hz, 635 samples (5) Reading a file-like object. >>> import requests >>> import io >>> example_url = "https://examples.obspy.org/loc_RJOB20050831023349.z" >>> stringio_obj = io.BytesIO(requests.get(example_url).content) >>> st = read(stringio_obj) >>> print(st) # doctest: +ELLIPSIS 1 Trace(s) in Stream: .RJOB..Z | 2005-08-31T02:33:49.850000Z - ... | 200.0 Hz, 12000 samples (6) Using 'starttime' and 'endtime' parameters >>> from obspy import read >>> dt = UTCDateTime("2005-08-31T02:34:00") >>> st = read("https://examples.obspy.org/loc_RJOB20050831023349.z", ... starttime=dt, endtime=dt+10) >>> print(st) # doctest: +ELLIPSIS 1 Trace(s) in Stream: .RJOB..Z | 2005-08-31T02:34:00.000000Z - ... | 200.0 Hz, 2001 samples """ # add default parameters to kwargs so sub-modules may handle them kwargs['starttime'] = starttime kwargs['endtime'] = endtime kwargs['nearest_sample'] = nearest_sample # create stream st = Stream() if pathname_or_url is None: # if no pathname or URL specified, return example stream st = _create_example_stream(headonly=headonly) elif not isinstance(pathname_or_url, (str, native_str)): # not a string - we assume a file-like object pathname_or_url.seek(0) try: # first try reading directly stream = _read(pathname_or_url, format, headonly, **kwargs) st.extend(stream.traces) except TypeError: # if this fails, create a temporary file which is read directly # from the file system pathname_or_url.seek(0) with NamedTemporaryFile() as fh: fh.write(pathname_or_url.read()) st.extend(_read(fh.name, format, headonly, **kwargs).traces) pathname_or_url.seek(0) elif "://" in pathname_or_url: # some URL # extract extension if any suffix = os.path.basename(pathname_or_url).partition('.')[2] or '.tmp' with NamedTemporaryFile(suffix=suffix) as fh: download_to_file(url=pathname_or_url, filename_or_buffer=fh) st.extend(_read(fh.name, format, headonly, **kwargs).traces) else: # some file name pathname = pathname_or_url for file in sorted(glob(pathname)): st.extend(_read(file, format, headonly, **kwargs).traces) if len(st) == 0: # try to give more specific information why the stream is empty if has_magic(pathname) and not glob(pathname): raise Exception("No file matching file pattern: %s" % pathname) elif not has_magic(pathname) and not os.path.isfile(pathname): raise IOError(2, "No such file or directory", pathname) # Only raise error if no start/end time has been set. This # will return an empty stream if the user chose a time window with # no data in it. # XXX: Might cause problems if the data is faulty and the user # set start/end time. Not sure what to do in this case. elif not starttime and not endtime: raise Exception("Cannot open file/files: %s" % pathname) # Trim if times are given. if headonly and (starttime or endtime or dtype): warnings.warn(_headonly_warning_msg, UserWarning) return st if starttime: st._ltrim(starttime, nearest_sample=nearest_sample) if endtime: st._rtrim(endtime, nearest_sample=nearest_sample) # convert to dtype if given if dtype: # For compatibility with NumPy 1.4 if isinstance(dtype, str): dtype = native_str(dtype) for tr in st: tr.data = np.require(tr.data, dtype) # applies calibration factor if apply_calib: for tr in st: tr.data = tr.data * tr.stats.calib return st
@uncompress_file
[docs]def _read(filename, format=None, headonly=False, **kwargs): """ Read a single file into a ObsPy Stream object. """ stream, format = _read_from_plugin('waveform', filename, format=format, headonly=headonly, **kwargs) # set _format identifier for each element for trace in stream: trace.stats._format = format return stream
[docs]def _create_example_stream(headonly=False): """ Create an example stream. Data arrays are stored in NumPy's NPZ format. The header information are fixed values. PAZ of the used instrument, needed to demonstrate simulate_seismometer() etc.:: paz = {'gain': 60077000.0, 'poles': [-0.037004+0.037016j, -0.037004-0.037016j, -251.33+0j, -131.04-467.29j, -131.04+467.29j], 'sensitivity': 2516778400.0, 'zeros': [0j, 0j]}} """ data_dir = os.path.join(os.path.dirname(__file__), "data") if not headonly: path = os.path.join(data_dir, "example.npz") data = np.load(path) st = Stream() for channel in ["EHZ", "EHN", "EHE"]: header = {'network': "BW", 'station': "RJOB", 'location': "", 'npts': 3000, 'starttime': UTCDateTime(2009, 8, 24, 0, 20, 3), 'sampling_rate': 100.0, 'calib': 1.0, 'back_azimuth': 100.0, 'inclination': 30.0} header['channel'] = channel if not headonly: st.append(Trace(data=data[channel], header=header)) else: st.append(Trace(header=header)) from obspy import read_inventory inv = read_inventory(os.path.join(data_dir, "BW_RJOB.xml")) st.attach_response(inv) return st
[docs]class Stream(object): """ List like object of multiple ObsPy Trace objects. :type traces: list of :class:`~obspy.core.trace.Trace`, optional :param traces: Initial list of ObsPy :class:`~obspy.core.trace.Trace` objects. .. rubric:: Basic Usage >>> trace1 = Trace() >>> trace2 = Trace() >>> stream = Stream(traces=[trace1, trace2]) >>> print(stream) # doctest: +ELLIPSIS 2 Trace(s) in Stream: ... .. rubric:: Supported Operations ``stream = streamA + streamB`` Merges all traces within the two Stream objects ``streamA`` and ``streamB`` into the new Stream object ``stream``. See also: :meth:`Stream.__add__`. ``stream += streamA`` Extends the Stream object ``stream`` with all traces from ``streamA``. See also: :meth:`Stream.__iadd__`. ``len(stream)`` Returns the number of Traces in the Stream object ``stream``. See also: :meth:`Stream.__len__`. ``str(stream)`` Contains the number of traces in the Stream object and returns the value of each Trace's __str__ method. See also: :meth:`Stream.__str__`. """
[docs] def __init__(self, traces=None): self.traces = [] if isinstance(traces, Trace): traces = [traces] if traces: self.traces.extend(traces)
[docs] def __add__(self, other): """ Add two streams or a stream with a single trace. :type other: :class:`~obspy.core.stream.Stream` or :class:`~obspy.core.trace.Trace` :param other: Stream or Trace object to add. :rtype: :class:`~obspy.core.stream.Stream` :returns: New Stream object containing references to the traces of the original streams .. rubric:: Examples 1. Adding two Streams >>> st1 = Stream([Trace(), Trace(), Trace()]) >>> len(st1) 3 >>> st2 = Stream([Trace(), Trace()]) >>> len(st2) 2 >>> stream = st1 + st2 >>> len(stream) 5 2. Adding Stream and Trace >>> stream2 = st1 + Trace() >>> len(stream2) 4 """ if isinstance(other, Trace): other = Stream([other]) if not isinstance(other, Stream): raise TypeError traces = self.traces + other.traces return self.__class__(traces=traces)
[docs] def __iadd__(self, other): """ Add two streams with self += other. It will extend the current Stream object with the traces of the given Stream. Traces will not be copied but references to the original traces will be appended. :type other: :class:`~obspy.core.stream.Stream` or :class:`~obspy.core.trace.Trace` :param other: Stream or Trace object to add. .. rubric:: Example >>> stream = Stream([Trace(), Trace(), Trace()]) >>> len(stream) 3 >>> stream += Stream([Trace(), Trace()]) >>> len(stream) 5 >>> stream += Trace() >>> len(stream) 6 """ if isinstance(other, Trace): other = Stream([other]) if not isinstance(other, Stream): raise TypeError self.extend(other.traces) return self
[docs] def __mul__(self, num): """ Create a new Stream containing num copies of this stream. :rtype num: int :param num: Number of copies. :returns: New ObsPy Stream object. .. rubric:: Example >>> from obspy import read >>> st = read() >>> len(st) 3 >>> st2 = st * 5 >>> len(st2) 15 """ if not isinstance(num, int): raise TypeError("Integer expected") from obspy import Stream st = Stream() for _i in range(num): st += self.copy() return st
[docs] def __iter__(self): """ Return a robust iterator for stream.traces. Doing this it is safe to remove traces from streams inside of for-loops using stream's :meth:`~obspy.core.stream.Stream.remove` method. Actually this creates a new iterator every time a trace is removed inside the for-loop. .. rubric:: Example >>> from obspy import Stream >>> st = Stream() >>> for component in ["1", "Z", "2", "3", "Z", "N", "E", "4", "5"]: ... channel = "EH" + component ... tr = Trace(header={'station': 'TEST', 'channel': channel}) ... st.append(tr) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 9 Trace(s) in Stream: .TEST..EH1 | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EHZ | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EH2 | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EH3 | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EHZ | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EHN | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EHE | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EH4 | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EH5 | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples >>> for tr in st: ... if tr.stats.channel[-1] not in ["Z", "N", "E"]: ... st.remove(tr) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 4 Trace(s) in Stream: .TEST..EHZ | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EHZ | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EHN | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples .TEST..EHE | 1970-01-01T00:00:00.000000Z - ... | 1.0 Hz, 0 samples """ return list(self.traces).__iter__()
[docs] def __nonzero__(self): """ A Stream is considered zero if has no Traces. """ return bool(len(self.traces))
[docs] def __len__(self): """ Return the number of Traces in the Stream object. .. rubric:: Example >>> stream = Stream([Trace(), Trace(), Trace()]) >>> len(stream) 3 """ return len(self.traces)
count = __len__
[docs] def __str__(self, extended=False): """ Return short summary string of the current stream. It will contain the number of Traces in the Stream and the return value of each Trace's :meth:`~obspy.core.trace.Trace.__str__` method. :type extended: bool, optional :param extended: This method will show only 20 traces by default. Enable this option to show all entries. .. rubric:: Example >>> stream = Stream([Trace(), Trace()]) >>> print(stream) # doctest: +ELLIPSIS 2 Trace(s) in Stream: ... """ # get longest id if self.traces: id_length = self and max(len(tr.id) for tr in self) or 0 else: id_length = 0 out = str(len(self.traces)) + ' Trace(s) in Stream:\n' if len(self.traces) <= 20 or extended is True: out = out + "\n".join([_i.__str__(id_length) for _i in self]) else: out = out + "\n" + self.traces[0].__str__() + "\n" + \ '...\n(%i other traces)\n...\n' % (len(self.traces) - 2) + \ self.traces[-1].__str__() + '\n\n[Use "print(' + \ 'Stream.__str__(extended=True))" to print all Traces]' return out
[docs] def _repr_pretty_(self, p, cycle): p.text(self.__str__(extended=p.verbose))
[docs] def __eq__(self, other): """ Implements rich comparison of Stream objects for "==" operator. :type other: :class:`~obspy.core.stream.Stream` :param other: Stream object for comparison. :rtype: bool :return: ``True`` if both Streams contain the same traces, i.e. after a sort operation going through both streams every trace should be equal according to Trace's :meth:`~obspy.core.trace.Trace.__eq__` operator. .. rubric:: Example >>> from obspy import read >>> st = read() >>> st2 = st.copy() >>> st is st2 False >>> st == st2 True """ if not isinstance(other, Stream): return False # this is maybe still not 100% satisfactory, the question here is if # two streams should be the same in comparison if one of the streams # has a duplicate trace. Using sets at the moment, two equal traces # in one of the Streams would lead to two non-equal Streams. # This is a bit more conservative and most likely the expected behavior # in most cases. self_sorted = self.select() self_sorted.sort() other_sorted = other.select() other_sorted.sort() if self_sorted.traces != other_sorted.traces: return False return True
[docs] def __ne__(self, other): """ Implements rich comparison of Stream objects for "!=" operator. .. rubric:: Example >>> from obspy import read >>> st = read() >>> st2 = st.copy() >>> st is st2 False >>> st != st2 False """ # Calls __eq__() and returns the opposite. return not self.__eq__(other)
[docs] def __lt__(self, other): """ Too ambiguous, throw an Error. """ raise NotImplementedError("Too ambiguous, therefore not implemented.")
[docs] def __le__(self, other): """ Too ambiguous, throw an Error. """ raise NotImplementedError("Too ambiguous, therefore not implemented.")
[docs] def __gt__(self, other): """ Too ambiguous, throw an Error. """ raise NotImplementedError("Too ambiguous, therefore not implemented.")
[docs] def __ge__(self, other): """ Too ambiguous, throw an Error. """ raise NotImplementedError("Too ambiguous, therefore not implemented.")
[docs] def __setitem__(self, index, trace): """ __setitem__ method of obspy.Stream objects. """ self.traces.__setitem__(index, trace)
[docs] def __getitem__(self, index): """ __getitem__ method of obspy.Stream objects. :return: Trace objects """ if isinstance(index, slice): return self.__class__(traces=self.traces.__getitem__(index)) else: return self.traces.__getitem__(index)
[docs] def __delitem__(self, index): """ Passes on the __delitem__ method to the underlying list of traces. """ return self.traces.__delitem__(index)
[docs] def __getslice__(self, i, j, k=1): """ __getslice__ method of obspy.Stream objects. :return: Stream object """ # see also https://docs.python.org/3/reference/datamodel.html return self.__class__(traces=self.traces[max(0, i):max(0, j):k])
[docs] def append(self, trace): """ Append a single Trace object to the current Stream object. :param trace: :class:`~obspy.core.stream.Trace` object. .. rubric:: Example >>> from obspy import read, Trace >>> st = read() >>> tr = Trace() >>> tr.stats.station = 'TEST' >>> st.append(tr) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 4 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples .TEST.. | 1970-01-01T00:00:00.000000Z ... | 1.0 Hz, 0 samples """ if isinstance(trace, Trace): self.traces.append(trace) else: msg = 'Append only supports a single Trace object as an argument.' raise TypeError(msg) return self
[docs] def extend(self, trace_list): """ Extend the current Stream object with a list of Trace objects. :param trace_list: list of :class:`~obspy.core.trace.Trace` objects or :class:`~obspy.core.stream.Stream`. .. rubric:: Example >>> from obspy import read, Trace >>> st = read() >>> tr1 = Trace() >>> tr1.stats.station = 'TEST1' >>> tr2 = Trace() >>> tr2.stats.station = 'TEST2' >>> st.extend([tr1, tr2]) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 5 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples .TEST1.. | 1970-01-01T00:00:00.000000Z ... | 1.0 Hz, 0 samples .TEST2.. | 1970-01-01T00:00:00.000000Z ... | 1.0 Hz, 0 samples """ if isinstance(trace_list, list): for _i in trace_list: # Make sure each item in the list is a trace. if not isinstance(_i, Trace): msg = 'Extend only accepts a list of Trace objects.' raise TypeError(msg) self.traces.extend(trace_list) elif isinstance(trace_list, Stream): self.traces.extend(trace_list.traces) else: msg = 'Extend only supports a list of Trace objects as argument.' raise TypeError(msg) return self
@deprecated( "'getGaps' has been renamed to " # noqa "'get_gaps'. Use that instead.")
[docs] def getGaps(self, *args, **kwargs): ''' DEPRECATED: 'getGaps' has been renamed to 'get_gaps'. Use that instead. ''' return self.get_gaps(*args, **kwargs)
[docs] def get_gaps(self, min_gap=None, max_gap=None): """ Determine all trace gaps/overlaps of the Stream object. :param min_gap: All gaps smaller than this value will be omitted. The value is assumed to be in seconds. Defaults to None. :param max_gap: All gaps larger than this value will be omitted. The value is assumed to be in seconds. Defaults to None. The returned list contains one item in the following form for each gap/ overlap: [network, station, location, channel, starttime of the gap, end time of the gap, duration of the gap, number of missing samples] Please be aware that no sorting and checking of stations, channels, ... is done. This method only compares the start and end times of the Traces. .. rubric:: Example Our example stream has no gaps: >>> from obspy import read, UTCDateTime >>> st = read() >>> st.get_gaps() [] >>> st.print_gaps() # doctest: +ELLIPSIS Source Last Sample ... Total: 0 gap(s) and 0 overlap(s) So let's make a copy of the first trace and cut both so that we end up with a gappy stream: >>> tr = st[0].copy() >>> t = UTCDateTime("2009-08-24T00:20:13.0") >>> st[0].trim(endtime=t) # doctest: +ELLIPSIS <...Trace object at 0x...> >>> tr.trim(starttime=t + 1) # doctest: +ELLIPSIS <...Trace object at 0x...> >>> st.append(tr) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st.get_gaps()[0] # doctest: +SKIP [['BW', 'RJOB', '', 'EHZ', UTCDateTime(2009, 8, 24, 0, 20, 13), UTCDateTime(2009, 8, 24, 0, 20, 14), 1.0, 99]] >>> st.print_gaps() # doctest: +ELLIPSIS Source Last Sample ... BW.RJOB..EHZ 2009-08-24T00:20:13.000000Z ... Total: 1 gap(s) and 0 overlap(s) """ # Create shallow copy of the traces to be able to sort them later on. copied_traces = copy.copy(self.traces) self.sort() gap_list = [] for _i in range(len(self.traces) - 1): # skip traces with different network, station, location or channel if self.traces[_i].id != self.traces[_i + 1].id: continue # different sampling rates should always result in a gap or overlap if self.traces[_i].stats.delta == self.traces[_i + 1].stats.delta: same_sampling_rate = True else: same_sampling_rate = False stats = self.traces[_i].stats stime = stats['endtime'] etime = self.traces[_i + 1].stats['starttime'] # last sample of earlier trace represents data up to time of last # sample (stats.endtime) plus one delta delta = etime.timestamp - (stime.timestamp + stats.delta) # Check that any overlap is not larger than the trace coverage if delta < 0: temp = self.traces[_i + 1].stats['endtime'].timestamp - \ etime.timestamp if (delta * -1) > temp: delta = -1 * temp # Check gap/overlap criteria if min_gap and delta < min_gap: continue if max_gap and delta > max_gap: continue # Number of missing samples nsamples = int(compatibility.round_away(math.fabs(delta) * stats['sampling_rate'])) if delta < 0: nsamples = -nsamples # skip if is equal to delta (1 / sampling rate) if same_sampling_rate and nsamples == 0: continue gap_list.append([stats['network'], stats['station'], stats['location'], stats['channel'], stime, etime, delta, nsamples]) # Set the original traces to not alter the stream object. self.traces = copied_traces return gap_list
[docs] def insert(self, position, object): """ Insert either a single Trace or a list of Traces before index. :param position: The Trace will be inserted at position. :param object: Single Trace object or list of Trace objects. """ if isinstance(object, Trace): self.traces.insert(position, object) elif isinstance(object, list): # Make sure each item in the list is a trace. for _i in object: if not isinstance(_i, Trace): msg = 'Trace object or a list of Trace objects expected!' raise TypeError(msg) # Insert each item of the list. for _i in range(len(object)): self.traces.insert(position + _i, object[_i]) elif isinstance(object, Stream): self.insert(position, object.traces) else: msg = 'Only accepts a Trace object or a list of Trace objects.' raise TypeError(msg) return self
[docs] def plot(self, *args, **kwargs): """ Create a waveform plot of the current ObsPy Stream object. :param outfile: Output file string. Also used to automatically determine the output format. Supported file formats depend on your matplotlib backend. Most backends support png, pdf, ps, eps and svg. Defaults to ``None``. :param format: Format of the graph picture. If no format is given the outfile parameter will be used to try to automatically determine the output format. If no format is found it defaults to png output. If no outfile is specified but a format is, than a binary imagestring will be returned. Defaults to ``None``. :param starttime: Start time of the graph as a :class:`~obspy.core.utcdatetime.UTCDateTime` object. If not set the graph will be plotted from the beginning. Defaults to ``None``. :param endtime: End time of the graph as a :class:`~obspy.core.utcdatetime.UTCDateTime` object. If not set the graph will be plotted until the end. Defaults to ``None``. :param fig: Use an existing matplotlib figure instance. Defaults to ``None``. :param automerge: If automerge is True, Traces with the same id will be merged. Defaults to ``True``. :param size: Size tuple in pixel for the output file. This corresponds to the resolution of the graph for vector formats. Defaults to ``(800, 250)`` pixel per channel for ``type='normal'`` or ``type='relative'``, ``(800, 600)`` for ``type='dayplot'``, and ``(1000, 600)`` for ``type='section'``. :param dpi: Dots per inch of the output file. This also affects the size of most elements in the graph (text, linewidth, ...). Defaults to ``100``. :param color: Color of the graph as a matplotlib color string as described below. If ``type='dayplot'`` a list/tuple of color strings is expected that will be periodically repeated for each line plotted. If ``type='section'`` then the values ``'network'``, ``'station'`` or ``'channel'`` are also accepted, and traces will be uniquely colored by the given information. Defaults to ``'black'`` or to ``('#B2000F', '#004C12', '#847200', '#0E01FF')`` for ``type='dayplot'``. :param bgcolor: Background color of the graph. Defaults to ``'white'``. :param face_color: Face color of the matplotlib canvas. Defaults to ``'white'``. :param transparent: Make all backgrounds transparent (True/False). This will override the ``bgcolor`` and ``face_color`` arguments. Defaults to ``False``. :param number_of_ticks: The number of ticks on the x-axis. Defaults to ``4``. :param tick_format: The way the time axis is formatted. Defaults to ``'%H:%M:%S'`` or ``'%.2f'`` if ``type='relative'``. :param tick_rotation: Tick rotation in degrees. Defaults to ``0``. :param handle: Whether or not to return the matplotlib figure instance after the plot has been created. Defaults to ``False``. :param method: By default, all traces with more than 400,000 samples will be plotted with a fast method that cannot be zoomed. Setting this argument to ``'full'`` will straight up plot the data. This results in a potentially worse performance but the interactive matplotlib view can be used properly. Defaults to 'fast'. :param type: Type may be set to either: ``'normal'`` to produce the standard plot; ``'dayplot'`` to create a one-day plot for a single Trace; ``'relative'`` to convert all date/time information to a relative scale starting the seismogram at 0 seconds; ``'section'`` to plot all seismograms in a single coordinate system shifted according to their distance from a reference point. Defaults to ``'normal'``. :param equal_scale: If enabled all plots are equally scaled. Defaults to ``True``. :param show: If True, show the plot interactively after plotting. This is ignored if any of ``outfile``, ``format``, ``handle``, or ``fig`` are specified. Defaults to ``True``. :param draw: If True, the figure canvas is explicitly re-drawn, which ensures that *existing* figures are fresh. It makes no difference for figures that are not yet visible. Defaults to ``True``. :param block: If True block call to showing plot. Only works if the active matplotlib backend supports it. Defaults to ``True``. :param linewidth: Float value in points of the line width. Defaults to ``1.0``. :param linestyle: Line style. Defaults to ``'-'`` :param grid_color: Color of the grid. Defaults to ``'black'``. :param grid_linewidth: Float value in points of the grid line width. Defaults to ``0.5``. :param grid_linestyle: Grid line style. Defaults to ``':'`` **Dayplot Parameters** The following parameters are only available if ``type='dayplot'`` is set. :param vertical_scaling_range: Determines how each line is scaled in its given space. Every line will be centered around its mean value and then clamped to fit its given space. This argument is the range in data units that will be used to clamp the data. If the range is smaller than the actual range, the lines' data may overshoot to other lines which is usually a desired effect. Larger ranges will result in a vertical padding. If ``0``, the actual range of the data will be used and no overshooting or additional padding will occur. If ``None`` the range will be chosen to be the 99.5-percentile of the actual range - so some values will overshoot. Defaults to ``None``. :param interval: This defines the interval length in minutes for one line. Defaults to ``15``. :param time_offset: Only used if ``type='dayplot'``. The difference between the timezone of the data (specified with the kwarg ``timezone``) and UTC time in hours. Will be displayed in a string. Defaults to the current offset of the system time to UTC time. :param timezone: Defines the name of the user defined time scale. Will be displayed in a string together with the actual offset defined in the kwarg ``time_offset``. Defaults to ``'local time'``. :param localization_dict: Enables limited localization of the dayplot through the usage of a dictionary. To change the labels to, e.g. German, use the following:: localization_dict={'time in': 'Zeit in', 'seconds': 'Sekunden', 'minutes': 'Minuten', 'hours': 'Stunden'} :param data_unit: If given, the scale of the data will be drawn on the right hand side in the form ``"%f {data_unit}"``. The unit is supposed to be a string containing the actual unit of the data. Can be a LaTeX expression if matplotlib has been built with LaTeX support, e.g., ``"$\\\\frac{m}{s}$"``. Be careful to escape the backslashes, or use r-prefixed strings, e.g., ``r"$\\\\frac{m}{s}$"``. Defaults to ``None``, meaning no scale is drawn. :param events: An optional list of events can be drawn on the plot if given. They will be displayed as yellow stars with optional annotations. They are given as a list of dictionaries. Each dictionary at least needs to have a "time" key, containing a UTCDateTime object with the origin time of the event. Furthermore every event can have an optional "text" key which will then be displayed as an annotation. Example:: events=[{"time": UTCDateTime(...), "text": "Event A"}, {...}] It can also be a :class:`~obspy.core.event.Catalog` object. In this case each event will be annotated with its corresponding Flinn-Engdahl region and the magnitude. Events can also be automatically downloaded with the help of obspy.clients.fdsn. Just pass a dictionary with a "min_magnitude" key, e.g. :: events={"min_magnitude": 5.5} Defaults to ``[]``. :param x_labels_size: Size of x labels in points or fontsize. Defaults to ``8``. :param y_labels_size: Size of y labels in points or fontsize. Defaults to ``8``. :param title_size: Size of the title in points or fontsize. Defaults to ``10``. :param subplots_adjust_left: The left side of the subplots of the figure in fraction of the figure width. Defaults to ``0.12``. :param subplots_adjust_right: The right side of the subplots of the figure in fraction of the figure width. Defaults to ``0.88``. :param subplots_adjust_top: The top side of the subplots of the figure in fraction of the figure width. Defaults to ``0.95``. :param subplots_adjust_bottom: The bottom side of the subplots of the figure in fraction of the figure width. Defaults to ``0.1``. :param right_vertical_labels: Whether or not to display labels on the right side of the dayplot. Defaults to ``False``. :param one_tick_per_line: Whether or not to display one tick per line. Defaults to ``False``. :param show_y_UTC_label: Whether or not to display the Y UTC vertical label. Defaults to ``True``. :param title: The title to display on top of the plot. Defaults to ``self.stream[0].id``. **Section Parameters** These parameters are only available if ``type='section'`` is set. To plot a record section the ObsPy header ``trace.stats.distance`` must be defined in meters (Default). Or ``trace.stats.coordinates.latitude`` & ``trace.stats.coordinates.longitude`` must be set if plotted in azimuthal distances (``dist_degree=True``) along with ``ev_coord``. :type scale: float, optional :param scale: Scale the traces width with this factor. Defaults to ``1.0``. :type vred: float, optional :param vred: Perform velocity reduction, in m/s. :type norm_method: str, optional :param norm_method: Defines how the traces are normalized, either against each ``trace`` or against the global maximum ``stream``. Defaults to ``trace``. :type offset_min: float or None, optional :param offset_min: Minimum offset in meters to plot. Defaults to minimum offset of all traces. :type offset_max: float or None, optional :param offset_max: Maximum offset in meters to plot. Defaults to maximum offset of all traces. :type dist_degree: bool, optional :param dist_degree: Plot trace distance in degree from epicenter. If ``True``, parameter ``ev_coord`` has to be defined. Defaults to ``False``. :type ev_coord: tuple or None, optional :param ev_coord: Event's coordinates as tuple ``(latitude, longitude)``. :type plot_dx: int, optional :param plot_dx: Spacing of ticks on the spatial x-axis. Either m or degree, depending on ``dist_degree``. :type recordstart: int or float, optional :param recordstart: Seconds to crop from the beginning. :type recordlength: int or float, optional :param recordlength: Length of the record section in seconds. :type alpha: float, optional :param alpha: Transparency of the traces between 0.0 - 1.0. Defaults to ``0.5``. :type time_down: bool, optional :param time_down: Flip the plot horizontally, time goes down. Defaults to ``False``, i.e., time goes up. :type reftime: :class:`~obspy.core.utcdatetime.UTCDateTime`, optional :param reftime: The reference time to which the time scale will refer. Defaults to the minimum start time of the visible traces. :type orientation: str, optional :param orientation: The orientation of the time axis, either ``'vertical'`` or ``'horizontal'``. Defaults to ``'vertical'``. **Relative Parameters** The following parameters are only available if ``type='relative'`` is set. :type reftime: :class:`~obspy.core.utcdatetime.UTCDateTime`, optional :param reftime: The reference time to which the relative scale will refer. Defaults to ``starttime``. .. rubric:: Color Options Colors can be specified as defined in the :mod:`matplotlib.colors` documentation. Short Version: For all color values, you can either use: * legal `HTML color names <https://www.w3.org/TR/css3-color/#html4>`_, e.g. ``'blue'``, * HTML hex strings, e.g. ``'#EE00FF'``, * pass an string of a R, G, B tuple, where each of the components is a float value in the range of 0 to 1, e.g. ``'(1, 0.25, 0.5)'``, or * use single letters for the basic built-in colors, such as ``'b'`` (blue), ``'g'`` (green), ``'r'`` (red), ``'c'`` (cyan), ``'m'`` (magenta), ``'y'`` (yellow), ``'k'`` (black), ``'w'`` (white). .. rubric:: Example >>> from obspy import read >>> st = read() >>> st.plot() # doctest: +SKIP .. plot:: from obspy import read st = read() st.plot() """ from obspy.imaging.waveform import WaveformPlotting waveform = WaveformPlotting(stream=self, *args, **kwargs) return waveform.plot_waveform(*args, **kwargs)
[docs] def spectrogram(self, **kwargs): """ Create a spectrogram plot for each trace in the stream. For details on kwargs that can be used to customize the spectrogram plot see :func:`obspy.imaging.spectrogram.spectrogram`. .. rubric:: Example >>> from obspy import read >>> st = read() >>> st[0].spectrogram() # doctest: +SKIP .. plot:: from obspy import read st = read() st[0].spectrogram() """ spec_list = [] for tr in self: spec = tr.spectrogram(**kwargs) spec_list.append(spec) return spec_list
[docs] def pop(self, index=(-1)): """ Remove and return the Trace object specified by index from the Stream. If no index is given, remove the last Trace. Passes on the pop() to self.traces. :param index: Index of the Trace object to be returned and removed. :returns: Removed Trace. .. rubric:: Example >>> from obspy import read >>> st = read() >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> tr = st.pop() >>> print(st) # doctest: +ELLIPSIS 2 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> print(tr) # doctest: +ELLIPSIS BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples """ return self.traces.pop(index)
@deprecated( "'printGaps' has been renamed to " # noqa "'print_gaps'. Use that instead.")
[docs] def printGaps(self, *args, **kwargs): ''' DEPRECATED: 'printGaps' has been renamed to 'print_gaps'. Use that instead. ''' return self.print_gaps(*args, **kwargs)
[docs] def print_gaps(self, min_gap=None, max_gap=None): """ Print gap/overlap list summary information of the Stream object. :param min_gap: All gaps smaller than this value will be omitted. The value is assumed to be in seconds. Defaults to None. :param max_gap: All gaps larger than this value will be omitted. The value is assumed to be in seconds. Defaults to None. .. rubric:: Example Our example stream has no gaps: >>> from obspy import read, UTCDateTime >>> st = read() >>> st.get_gaps() [] >>> st.print_gaps() # doctest: +ELLIPSIS Source Last Sample Next Sample ... Total: 0 gap(s) and 0 overlap(s) So let's make a copy of the first trace and cut both so that we end up with a gappy stream: >>> tr = st[0].copy() >>> t = UTCDateTime("2009-08-24T00:20:13.0") >>> st[0].trim(endtime=t) # doctest: +ELLIPSIS <...Trace object at 0x...> >>> tr.trim(starttime=t+1) # doctest: +ELLIPSIS <...Trace object at 0x...> >>> st.append(tr) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st.get_gaps() # doctest: +ELLIPSIS [[..., UTCDateTime(2009, 8, 24, 0, 20, 13), ... >>> st.print_gaps() # doctest: +ELLIPSIS Source Last Sample ... BW.RJOB..EHZ 2009-08-24T00:20:13.000000Z ... Total: 1 gap(s) and 0 overlap(s) And finally let us create some overlapping traces: >>> st = read() >>> tr = st[0].copy() >>> t = UTCDateTime("2009-08-24T00:20:13.0") >>> st[0].trim(endtime=t) # doctest: +ELLIPSIS <...Trace object at 0x...> >>> tr.trim(starttime=t-1) # doctest: +ELLIPSIS <...Trace object at 0x...> >>> st.append(tr) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st.get_gaps() # doctest: +ELLIPSIS [[...'EHZ', UTCDateTime(2009, 8, 24, 0, 20, 13), ... >>> st.print_gaps() # doctest: +ELLIPSIS Source Last Sample ... BW.RJOB..EHZ 2009-08-24T00:20:13.000000Z ... Total: 0 gap(s) and 1 overlap(s) """ result = self.get_gaps(min_gap, max_gap) print("%-17s %-27s %-27s %-15s %-8s" % ('Source', 'Last Sample', 'Next Sample', 'Delta', 'Samples')) gaps = 0 overlaps = 0 for r in result: if r[6] > 0: gaps += 1 else: overlaps += 1 print("%-17s %-27s %-27s %-15.6f %-8d" % ('.'.join(r[0:4]), r[4], r[5], r[6], r[7])) print("Total: %d gap(s) and %d overlap(s)" % (gaps, overlaps))
[docs] def remove(self, trace): """ Remove the first occurrence of the specified Trace object in the Stream object. Passes on the remove() call to self.traces. :param trace: Trace object to be removed from Stream. .. rubric:: Example This example shows how to delete all "E" component traces in a stream: >>> from obspy import read >>> st = read() >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> for tr in st.select(component="E"): ... st.remove(tr) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 2 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples """ self.traces.remove(trace) return self
[docs] def reverse(self): """ Reverse the Traces of the Stream object in place. .. rubric:: Example >>> from obspy import read >>> st = read() >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> st.reverse() # doctest: +ELLIPSIS <...Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples """ self.traces.reverse() return self
[docs] def sort(self, keys=['network', 'station', 'location', 'channel', 'starttime', 'endtime'], reverse=False): """ Sort the traces in the Stream object. The traces will be sorted according to the keys list. It will be sorted by the first item first, then by the second and so on. It will always be sorted from low to high and from A to Z. :type keys: list, optional :param keys: List containing the values according to which the traces will be sorted. They will be sorted by the first item first and then by the second item and so on. Always available items: 'network', 'station', 'channel', 'location', 'starttime', 'endtime', 'sampling_rate', 'npts', 'dataquality' Defaults to ['network', 'station', 'location', 'channel', 'starttime', 'endtime']. :type reverse: bool :param reverse: Reverts sorting order to descending. .. rubric:: Example >>> from obspy import read >>> st = read() >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> st.sort() # doctest: +ELLIPSIS <...Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples """ # check if list msg = "keys must be a list of strings. Always available items to " + \ "sort after: \n'network', 'station', 'channel', 'location', " + \ "'starttime', 'endtime', 'sampling_rate', 'npts', 'dataquality'" if not isinstance(keys, list): raise TypeError(msg) # Loop over all keys in reversed order. for _i in keys[::-1]: self.traces.sort(key=lambda x: x.stats[_i], reverse=reverse) return self
[docs] def write(self, filename, format, **kwargs): """ Save stream into a file. :type filename: str :param filename: The name of the file to write. :type format: str :param format: The file format to use (e.g. ``"MSEED"``). See the `Supported Formats`_ section below for a list of supported formats. :param kwargs: Additional keyword arguments passed to the underlying waveform writer method. .. rubric:: Example >>> from obspy import read >>> st = read() # doctest: +SKIP >>> st.write("example.mseed", format="MSEED") # doctest: +SKIP Writing single traces into files with meaningful filenames can be done e.g. using trace.id >>> for tr in st: #doctest: +SKIP ... tr.write(tr.id + ".MSEED", format="MSEED") #doctest: +SKIP .. rubric:: _`Supported Formats` Additional ObsPy modules extend the parameters of the :meth:`~obspy.core.stream.Stream.write` method. The following table summarizes all known formats currently available for ObsPy. Please refer to the `Linked Function Call`_ of each module for any extra options available. %s """ # Check all traces for masked arrays and raise exception. for trace in self.traces: if isinstance(trace.data, np.ma.masked_array): msg = 'Masked array writing is not supported. You can use ' + \ 'np.array.filled() to convert the masked array to a ' + \ 'normal array.' raise NotImplementedError(msg) format = format.upper() try: # get format specific entry point format_ep = ENTRY_POINTS['waveform_write'][format] # search writeFormat method for given entry point write_format = load_entry_point( format_ep.dist.key, 'obspy.plugin.waveform.%s' % (format_ep.name), 'writeFormat') except (IndexError, ImportError, KeyError): msg = "Writing format \"%s\" is not supported. Supported types: %s" raise TypeError(msg % (format, ', '.join(ENTRY_POINTS['waveform_write']))) write_format(self, filename, **kwargs)
[docs] def trim(self, starttime=None, endtime=None, pad=False, nearest_sample=True, fill_value=None): """ Cut all traces of this Stream object to given start and end time. :type starttime: :class:`~obspy.core.utcdatetime.UTCDateTime`, optional :param starttime: Specify the start time. :type endtime: :class:`~obspy.core.utcdatetime.UTCDateTime`, optional :param endtime: Specify the end time. :type pad: bool, optional :param pad: Gives the possibility to trim at time points outside the time frame of the original trace, filling the trace with the given ``fill_value``. Defaults to ``False``. :type nearest_sample: bool, optional :param nearest_sample: If set to ``True``, the closest sample is selected, if set to ``False``, the inner (next sample for a start time border, previous sample for an end time border) sample containing the time is selected. Defaults to ``True``. Given the following trace containing 6 samples, "|" are the sample points, "A" is the requested starttime:: | |A | | B | | 1 2 3 4 5 6 ``nearest_sample=True`` will select samples 2-5, ``nearest_sample=False`` will select samples 3-4 only. :type fill_value: int, float or ``None``, optional :param fill_value: Fill value for gaps. Defaults to ``None``. Traces will be converted to NumPy masked arrays if no value is given and gaps are present. .. note:: This operation is performed in place on the actual data arrays. The raw data will no longer be accessible afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. .. rubric:: Example >>> st = read() >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> dt = UTCDateTime("2009-08-24T00:20:20") >>> st.trim(dt, dt + 5) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:20.000000Z ... | 100.0 Hz, 501 samples BW.RJOB..EHN | 2009-08-24T00:20:20.000000Z ... | 100.0 Hz, 501 samples BW.RJOB..EHE | 2009-08-24T00:20:20.000000Z ... | 100.0 Hz, 501 samples """ if not self: return # select start/end time fitting to a sample point of the first trace if nearest_sample: tr = self.traces[0] if starttime: delta = compatibility.round_away( (starttime - tr.stats.starttime) * tr.stats.sampling_rate) starttime = tr.stats.starttime + delta * tr.stats.delta if endtime: delta = compatibility.round_away( (endtime - tr.stats.endtime) * tr.stats.sampling_rate) # delta is negative! endtime = tr.stats.endtime + delta * tr.stats.delta for trace in self.traces: trace.trim(starttime, endtime, pad=pad, nearest_sample=nearest_sample, fill_value=fill_value) # remove empty traces after trimming self.traces = [_i for _i in self.traces if _i.stats.npts] return self
[docs] def _ltrim(self, starttime, pad=False, nearest_sample=True): """ Cut all traces of this Stream object to given start time. For more info see :meth:`~obspy.core.trace.Trace._ltrim`. """ for trace in self.traces: trace.trim(starttime=starttime, pad=pad, nearest_sample=nearest_sample) # remove empty traces after trimming self.traces = [tr for tr in self.traces if tr.stats.npts] return self
[docs] def _rtrim(self, endtime, pad=False, nearest_sample=True): """ Cut all traces of this Stream object to given end time. For more info see :meth:`~obspy.core.trace.Trace._rtrim`. """ for trace in self.traces: trace.trim(endtime=endtime, pad=pad, nearest_sample=nearest_sample) # remove empty traces after trimming self.traces = [tr for tr in self.traces if tr.stats.npts] return self
[docs] def cutout(self, starttime, endtime): """ Cut the given time range out of all traces of this Stream object. :type starttime: :class:`~obspy.core.utcdatetime.UTCDateTime` :param starttime: Start of time span to remove from stream. :type endtime: :class:`~obspy.core.utcdatetime.UTCDateTime` :param endtime: End of time span to remove from stream. .. rubric:: Example >>> st = read() >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> t1 = UTCDateTime("2009-08-24T00:20:06") >>> t2 = UTCDateTime("2009-08-24T00:20:11") >>> st.cutout(t1, t2) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 6 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 301 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 301 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 301 samples BW.RJOB..EHZ | 2009-08-24T00:20:11.000000Z ... | 100.0 Hz, 2200 samples BW.RJOB..EHN | 2009-08-24T00:20:11.000000Z ... | 100.0 Hz, 2200 samples BW.RJOB..EHE | 2009-08-24T00:20:11.000000Z ... | 100.0 Hz, 2200 samples """ tmp = self.slice(endtime=starttime, keep_empty_traces=False) tmp += self.slice(starttime=endtime, keep_empty_traces=False) self.traces = tmp.traces return self
[docs] def slice(self, starttime=None, endtime=None, keep_empty_traces=False, nearest_sample=True): """ Return new Stream object cut to the given start and end time. :type starttime: :class:`~obspy.core.utcdatetime.UTCDateTime` :param starttime: Specify the start time of all traces. :type endtime: :class:`~obspy.core.utcdatetime.UTCDateTime` :param endtime: Specify the end time of all traces. :type keep_empty_traces: bool, optional :param keep_empty_traces: Empty traces will be kept if set to ``True``. Defaults to ``False``. :type nearest_sample: bool, optional :param nearest_sample: If set to ``True``, the closest sample is selected, if set to ``False``, the inner (next sample for a start time border, previous sample for an end time border) sample containing the time is selected. Defaults to ``True``. Given the following trace containing 6 samples, "|" are the sample points, "A" is the requested starttime:: | |A | | B | | 1 2 3 4 5 6 ``nearest_sample=True`` will select samples 2-5, ``nearest_sample=False`` will select samples 3-4 only. :return: :class:`~obspy.core.stream.Stream` .. note:: The basic idea of :meth:`~obspy.core.stream.Stream.slice` is to avoid copying the sample data in memory. So sample data in the resulting :class:`~obspy.core.stream.Stream` object contains only a reference to the original traces. .. rubric:: Example >>> st = read() >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> dt = UTCDateTime("2009-08-24T00:20:20") >>> st = st.slice(dt, dt + 5) >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:20.000000Z ... | 100.0 Hz, 501 samples BW.RJOB..EHN | 2009-08-24T00:20:20.000000Z ... | 100.0 Hz, 501 samples BW.RJOB..EHE | 2009-08-24T00:20:20.000000Z ... | 100.0 Hz, 501 samples """ tmp = copy.copy(self) tmp.traces = [] new = tmp.copy() for trace in self: sliced_trace = trace.slice(starttime=starttime, endtime=endtime, nearest_sample=nearest_sample) if keep_empty_traces is False and not sliced_trace.stats.npts: continue new.append(sliced_trace) return new
[docs] def slide(self, window_length, step, offset=0, include_partial_windows=False, nearest_sample=True): """ Generator yielding equal length sliding windows of the Stream. Please keep in mind that it only returns a new view of the original data. Any modifications are applied to the original data as well. If you don't want this you have to create a copy of the yielded windows. Also be aware that if you modify the original data and you have overlapping windows, all following windows are affected as well. Not all yielded windows must have the same number of traces. The algorithm will determine the maximal temporal extents by analysing all Traces and then creates windows based on these times. .. rubric:: Example >>> import obspy >>> st = obspy.read() >>> for windowed_st in st.slide(window_length=10.0, step=10.0): ... print(windowed_st) ... print("---") # doctest: +NORMALIZE_WHITESPACE +ELLIPSIS 3 Trace(s) in Stream: ... | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:13.000000Z | ... ... | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:13.000000Z | ... ... | 2009-08-24T00:20:03.000000Z - 2009-08-24T00:20:13.000000Z | ... --- 3 Trace(s) in Stream: ... | 2009-08-24T00:20:13.000000Z - 2009-08-24T00:20:23.000000Z | ... ... | 2009-08-24T00:20:13.000000Z - 2009-08-24T00:20:23.000000Z | ... ... | 2009-08-24T00:20:13.000000Z - 2009-08-24T00:20:23.000000Z | ... :param window_length: The length of each window in seconds. :type window_length: float :param step: The step between the start times of two successive windows in seconds. Can be negative if an offset is given. :type step: float :param offset: The offset of the first window in seconds relative to the start time of the whole interval. :type offset: float :param include_partial_windows: Determines if windows that are shorter then 99.9 % of the desired length are returned. :type include_partial_windows: bool :param nearest_sample: If set to ``True``, the closest sample is selected, if set to ``False``, the inner (next sample for a start time border, previous sample for an end time border) sample containing the time is selected. Defaults to ``True``. Given the following trace containing 6 samples, "|" are the sample points, "A" is the requested starttime:: | |A | | B | | 1 2 3 4 5 6 ``nearest_sample=True`` will select samples 2-5, ``nearest_sample=False`` will select samples 3-4 only. :type nearest_sample: bool, optional """ starttime = min(tr.stats.starttime for tr in self) endtime = max(tr.stats.endtime for tr in self) windows = get_window_times( starttime=starttime, endtime=endtime, window_length=window_length, step=step, offset=offset, include_partial_windows=include_partial_windows) if len(windows) < 1: raise StopIteration for start, stop in windows: temp = self.slice(start, stop, nearest_sample=nearest_sample) # It might happen that there is a time frame where there are no # windows, e.g. two traces separated by a large gap. if not temp: continue yield temp raise StopIteration
[docs] def select(self, network=None, station=None, location=None, channel=None, sampling_rate=None, npts=None, component=None, id=None): """ Return new Stream object only with these traces that match the given stats criteria (e.g. all traces with ``channel="EHZ"``). .. rubric:: Examples >>> from obspy import read >>> st = read() >>> st2 = st.select(station="R*") >>> print(st2) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> st2 = st.select(id="BW.RJOB..EHZ") >>> print(st2) # doctest: +ELLIPSIS 1 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> st2 = st.select(component="Z") >>> print(st2) # doctest: +ELLIPSIS 1 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> st2 = st.select(network="CZ") >>> print(st2) # doctest: +NORMALIZE_WHITESPACE 0 Trace(s) in Stream: .. warning:: A new Stream object is returned but the traces it contains are just aliases to the traces of the original stream. Does not copy the data but only passes a reference. All keyword arguments except for ``component`` are tested directly against the respective entry in the :class:`~obspy.core.trace.Stats` dictionary. If a string for ``component`` is given (should be a single letter) it is tested against the last letter of the ``Trace.stats.channel`` entry. Alternatively, ``channel`` may have the last one or two letters wildcarded (e.g. ``channel="EH*"``) to select all components with a common band/instrument code. All other selection criteria that accept strings (network, station, location) may also contain Unix style wildcards (``*``, ``?``, ...). """ # make given component letter uppercase (if e.g. "z" is given) if component and channel: component = component.upper() channel = channel.upper() if channel[-1] != "*" and component != channel[-1]: msg = "Selection criteria for channel and component are " + \ "mutually exclusive!" raise ValueError(msg) traces = [] for trace in self: # skip trace if any given criterion is not matched if id and not fnmatch.fnmatch(trace.id.upper(), id.upper()): continue if network is not None: if not fnmatch.fnmatch(trace.stats.network.upper(), network.upper()): continue if station is not None: if not fnmatch.fnmatch(trace.stats.station.upper(), station.upper()): continue if location is not None: if not fnmatch.fnmatch(trace.stats.location.upper(), location.upper()): continue if channel is not None: if not fnmatch.fnmatch(trace.stats.channel.upper(), channel.upper()): continue if sampling_rate is not None: if float(sampling_rate) != trace.stats.sampling_rate: continue if npts is not None and int(npts) != trace.stats.npts: continue if component is not None: if len(trace.stats.channel) < 3: continue if not fnmatch.fnmatch(trace.stats.channel[-1].upper(), component.upper()): continue traces.append(trace) return self.__class__(traces=traces)
[docs] def verify(self): """ Verify all traces of current Stream against available meta data. .. rubric:: Example >>> from obspy import Trace, Stream >>> tr = Trace(data=np.array([1, 2, 3, 4])) >>> tr.stats.npts = 100 >>> st = Stream([tr]) >>> st.verify() #doctest: +ELLIPSIS Traceback (most recent call last): ... Exception: ntps(100) differs from data size(4) """ for trace in self: trace.verify() return self
[docs] def _merge_checks(self): """ Sanity checks for merging. """ sr = {} dtype = {} calib = {} for trace in self.traces: # skip empty traces if len(trace) == 0: continue # Check sampling rate. sr.setdefault(trace.id, trace.stats.sampling_rate) if trace.stats.sampling_rate != sr[trace.id]: msg = "Can't merge traces with same ids but differing " + \ "sampling rates!" raise Exception(msg) # Check dtype. dtype.setdefault(trace.id, trace.data.dtype) if trace.data.dtype != dtype[trace.id]: msg = "Can't merge traces with same ids but differing " + \ "data types!" raise Exception(msg) # Check calibration factor. calib.setdefault(trace.id, trace.stats.calib) if trace.stats.calib != calib[trace.id]: msg = "Can't merge traces with same ids but differing " + \ "calibration factors.!" raise Exception(msg)
[docs] def merge(self, method=0, fill_value=None, interpolation_samples=0, **kwargs): """ Merge ObsPy Trace objects with same IDs. :type method: int, optional :param method: Methodology to handle overlaps/gaps of traces. Defaults to ``0``. See :meth:`obspy.core.trace.Trace.__add__` for details on methods ``0`` and ``1``, see :meth:`obspy.core.stream.Stream._cleanup` for details on method ``-1``. Any merge operation performs a cleanup merge as a first step (method ``-1``). :type fill_value: int, float, str or ``None``, optional :param fill_value: Fill value for gaps. Defaults to ``None``. Traces will be converted to NumPy masked arrays if no value is given and gaps are present. The value ``'latest'`` will use the latest value before the gap. If value ``'interpolate'`` is provided, missing values are linearly interpolated (not changing the data type e.g. of integer valued traces). Not used for ``method=-1``. :type interpolation_samples: int, optional :param interpolation_samples: Used only for ``method=1``. It specifies the number of samples which are used to interpolate between overlapping traces. Default to ``0``. If set to ``-1`` all overlapping samples are interpolated. Importing waveform data containing gaps or overlaps results into a :class:`~obspy.core.stream.Stream` object with multiple traces having the same identifier. This method tries to merge such traces inplace, thus returning nothing. Merged trace data will be converted into a NumPy :class:`~numpy.ma.MaskedArray` type if any gaps are present. This behavior may be prevented by setting the ``fill_value`` parameter. The ``method`` argument controls the handling of overlapping data values. """ def listsort(order, current): """ Helper method for keeping trace's ordering """ try: return order.index(current) except ValueError: return -1 self._cleanup(**kwargs) if method == -1: return # check sampling rates and dtypes self._merge_checks() # remember order of traces order = [id(i) for i in self.traces] # order matters! self.sort(keys=['network', 'station', 'location', 'channel', 'starttime', 'endtime']) # build up dictionary with with lists of traces with same ids traces_dict = {} # using pop() and try-except saves memory try: while True: trace = self.traces.pop(0) # skip empty traces if len(trace) == 0: continue _id = trace.get_id() if _id not in traces_dict: traces_dict[_id] = [trace] else: traces_dict[_id].append(trace) except IndexError: pass # clear traces of current stream self.traces = [] # loop through ids for _id in traces_dict.keys(): cur_trace = traces_dict[_id].pop(0) # loop through traces of same id for _i in range(len(traces_dict[_id])): trace = traces_dict[_id].pop(0) # disable sanity checks because there are already done cur_trace = cur_trace.__add__( trace, method, fill_value=fill_value, sanity_checks=False, interpolation_samples=interpolation_samples) self.traces.append(cur_trace) # trying to restore order, newly created traces are placed at # start self.traces.sort(key=lambda x: listsort(order, id(x))) return self
[docs] def simulate(self, paz_remove=None, paz_simulate=None, remove_sensitivity=True, simulate_sensitivity=True, **kwargs): """ Correct for instrument response / Simulate new instrument response. :type paz_remove: dict, None :param paz_remove: Dictionary containing keys ``'poles'``, ``'zeros'``, ``'gain'`` (A0 normalization factor). Poles and zeros must be a list of complex floating point numbers, gain must be of type float. Poles and Zeros are assumed to correct to m/s, SEED convention. Use ``None`` for no inverse filtering. Use ``'self'`` to use paz AttribDict in ``trace.stats`` for every trace in stream. :type paz_simulate: dict, None :param paz_simulate: Dictionary containing keys ``'poles'``, ``'zeros'``, ``'gain'``. Poles and zeros must be a list of complex floating point numbers, gain must be of type float. Or ``None`` for no simulation. :type remove_sensitivity: bool :param remove_sensitivity: Determines if data is divided by ``paz_remove['sensitivity']`` to correct for overall sensitivity of recording instrument (seismometer/digitizer) during instrument correction. :type simulate_sensitivity: bool :param simulate_sensitivity: Determines if data is multiplied with ``paz_simulate['sensitivity']`` to simulate overall sensitivity of new instrument (seismometer/digitizer) during instrument simulation. This function corrects for the original instrument response given by ``paz_remove`` and/or simulates a new instrument response given by ``paz_simulate``. For additional information and more options to control the instrument correction/simulation (e.g. water level, demeaning, tapering, ...) see :func:`~obspy.signal.invsim.simulate_seismometer`. The keywords `paz_remove` and `paz_simulate` are expected to be dictionaries containing information on poles, zeros and gain (and usually also sensitivity). If both ``paz_remove`` and ``paz_simulate`` are specified, both steps are performed in one go in the frequency domain, otherwise only the specified step is performed. .. note:: Instead of the builtin deconvolution based on Poles and Zeros information, the deconvolution can be performed using evalresp instead by using the option `seedresp` (see documentation of :func:`~obspy.signal.invsim.simulate_seismometer` and the `ObsPy Tutorial <https://docs.obspy.org/master/tutorial/code_snippets/\ seismometer_correction_simulation.html#using-a-resp-file>`_. .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. This also makes an entry with information on the applied processing in ``stats.processing`` of every trace. .. rubric:: Example >>> from obspy import read >>> from obspy.signal.invsim import corn_freq_2_paz >>> st = read() >>> paz_sts2 = {'poles': [-0.037004+0.037016j, -0.037004-0.037016j, ... -251.33+0j, ... -131.04-467.29j, -131.04+467.29j], ... 'zeros': [0j, 0j], ... 'gain': 60077000.0, ... 'sensitivity': 2516778400.0} >>> paz_1hz = corn_freq_2_paz(1.0, damp=0.707) >>> st.simulate(paz_remove=paz_sts2, paz_simulate=paz_1hz) ... # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st.plot() # doctest: +SKIP .. plot:: from obspy import read from obspy.signal.invsim import corn_freq_2_paz st = read() paz_sts2 = {'poles': [-0.037004+0.037016j, -0.037004-0.037016j, -251.33+0j, -131.04-467.29j, -131.04+467.29j], 'zeros': [0j, 0j], 'gain': 60077000.0, 'sensitivity': 2516778400.0} paz_1hz = corn_freq_2_paz(1.0, damp=0.707) paz_1hz['sensitivity'] = 1.0 st.simulate(paz_remove=paz_sts2, paz_simulate=paz_1hz) st.plot() """ for tr in self: tr.simulate(paz_remove=paz_remove, paz_simulate=paz_simulate, remove_sensitivity=remove_sensitivity, simulate_sensitivity=simulate_sensitivity, **kwargs) return self
@raise_if_masked
[docs] def filter(self, type, **options): """ Filter the data of all traces in the Stream. :type type: str :param type: String that specifies which filter is applied (e.g. ``"bandpass"``). See the `Supported Filter`_ section below for further details. :param options: Necessary keyword arguments for the respective filter that will be passed on. (e.g. ``freqmin=1.0``, ``freqmax=20.0`` for ``"bandpass"``) .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. This also makes an entry with information on the applied processing in ``stats.processing`` of every trace. .. rubric:: _`Supported Filter` ``'bandpass'`` Butterworth-Bandpass (uses :func:`obspy.signal.filter.bandpass`). ``'bandstop'`` Butterworth-Bandstop (uses :func:`obspy.signal.filter.bandstop`). ``'lowpass'`` Butterworth-Lowpass (uses :func:`obspy.signal.filter.lowpass`). ``'highpass'`` Butterworth-Highpass (uses :func:`obspy.signal.filter.highpass`). ``'lowpass_cheby_2'`` Cheby2-Lowpass (uses :func:`obspy.signal.filter.lowpass_cheby_2`). ``'lowpass_fir'`` (experimental) FIR-Lowpass (uses :func:`obspy.signal.filter.lowpass_fir`). ``'remez_fir'`` (experimental) Minimax optimal bandpass using Remez algorithm (uses :func:`obspy.signal.filter.remez_fir`). .. rubric:: Example >>> from obspy import read >>> st = read() >>> st.filter("highpass", freq=1.0) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st.plot() # doctest: +SKIP .. plot:: from obspy import read st = read() st.filter("highpass", freq=1.0) st.plot() """ for tr in self: tr.filter(type, **options) return self
[docs] def trigger(self, type, **options): """ Run a triggering algorithm on all traces in the stream. :param type: String that specifies which trigger is applied (e.g. ``'recstalta'``). See the `Supported Trigger`_ section below for further details. :param options: Necessary keyword arguments for the respective trigger that will be passed on. (e.g. ``sta=3``, ``lta=10``) Arguments ``sta`` and ``lta`` (seconds) will be mapped to ``nsta`` and ``nlta`` (samples) by multiplying with sampling rate of trace. (e.g. ``sta=3``, ``lta=10`` would call the trigger with 3 and 10 seconds average, respectively) .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. This also makes an entry with information on the applied processing in ``stats.processing`` of every trace. .. rubric:: _`Supported Trigger` ``'classicstalta'`` Computes the classic STA/LTA characteristic function (uses :func:`obspy.signal.trigger.classic_sta_lta`). ``'recstalta'`` Recursive STA/LTA (uses :func:`obspy.signal.trigger.recursive_sta_lta`). ``'recstaltapy'`` Recursive STA/LTA written in Python (uses :func:`obspy.signal.trigger.recursive_sta_lta_py`). ``'delayedstalta'`` Delayed STA/LTA. (uses :func:`obspy.signal.trigger.delayed_sta_lta`). ``'carlstatrig'`` Computes the carl_sta_trig characteristic function (uses :func:`obspy.signal.trigger.carl_sta_trig`). ``'zdetect'`` Z-detector (uses :func:`obspy.signal.trigger.z_detect`). .. rubric:: Example >>> from obspy import read >>> st = read() >>> st.filter("highpass", freq=1.0) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st.plot() # doctest: +SKIP >>> st.trigger('recstalta', sta=1, lta=4) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st.plot() # doctest: +SKIP .. plot:: from obspy import read st = read() st.filter("highpass", freq=1.0) st.plot() st.trigger('recstalta', sta=1, lta=4) st.plot() """ for tr in self: tr.trigger(type, **options) return self
[docs] def resample(self, sampling_rate, window='hanning', no_filter=True, strict_length=False): """ Resample data in all traces of stream using Fourier method. :type sampling_rate: float :param sampling_rate: The sampling rate of the resampled signal. :type window: array_like, callable, str, float, or tuple, optional :param window: Specifies the window applied to the signal in the Fourier domain. Defaults ``'hanning'`` window. See :func:`scipy.signal.resample` for details. :type no_filter: bool, optional :param no_filter: Deactivates automatic filtering if set to ``True``. Defaults to ``True``. :type strict_length: bool, optional :param strict_length: Leave traces unchanged for which end time of trace would change. Defaults to ``False``. .. note:: The :class:`~Stream` object has three different methods to change the sampling rate of its data: :meth:`~.resample`, :meth:`~.decimate`, and :meth:`~.interpolate` Make sure to choose the most appropriate one for the problem at hand. .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. This also makes an entry with information on the applied processing in ``stats.processing`` of every trace. Uses :func:`scipy.signal.resample`. Because a Fourier method is used, the signal is assumed to be periodic. .. rubric:: Example >>> st = read() >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 100.0 Hz, 3000 samples >>> st.resample(10.0) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03.000000Z ... | 10.0 Hz, 300 samples BW.RJOB..EHN | 2009-08-24T00:20:03.000000Z ... | 10.0 Hz, 300 samples BW.RJOB..EHE | 2009-08-24T00:20:03.000000Z ... | 10.0 Hz, 300 samples """ for tr in self: tr.resample(sampling_rate, window=native_str(window), no_filter=no_filter, strict_length=strict_length) return self
[docs] def decimate(self, factor, no_filter=False, strict_length=False): """ Downsample data in all traces of stream by an integer factor. :type factor: int :param factor: Factor by which the sampling rate is lowered by decimation. :type no_filter: bool, optional :param no_filter: Deactivates automatic filtering if set to ``True``. Defaults to ``False``. :type strict_length: bool, optional :param strict_length: Leave traces unchanged for which end time of trace would change. Defaults to ``False``. Currently a simple integer decimation is implemented. Only every decimation_factor-th sample remains in the trace, all other samples are thrown away. Prior to decimation a lowpass filter is applied to ensure no aliasing artifacts are introduced. The automatic filtering can be deactivated with ``no_filter=True``. If the length of the data array modulo ``decimation_factor`` is not zero then the end time of the trace is changing on sub-sample scale. To abort downsampling in case of changing end times set ``strict_length=True``. .. note:: The :class:`~Stream` object has three different methods to change the sampling rate of its data: :meth:`~.resample`, :meth:`~.decimate`, and :meth:`~.interpolate` Make sure to choose the most appropriate one for the problem at hand. .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. This also makes an entry with information on the applied processing in ``stats.processing`` of every trace. .. rubric:: Example For the example we switch off the automatic pre-filtering so that the effect of the downsampling routine becomes clearer. >>> from obspy import Trace, Stream >>> tr = Trace(data=np.arange(10)) >>> st = Stream(traces=[tr]) >>> tr.stats.sampling_rate 1.0 >>> tr.data array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) >>> st.decimate(4, strict_length=False, no_filter=True) ... # doctest: +ELLIPSIS <...Stream object at 0x...> >>> tr.stats.sampling_rate 0.25 >>> tr.data array([0, 4, 8]) """ for tr in self: tr.decimate(factor, no_filter=no_filter, strict_length=strict_length) return self
[docs] def max(self): """ Get the values of the absolute maximum amplitudes of all traces in the stream. See :meth:`~obspy.core.trace.Trace.max`. :return: List of values of absolute maxima of all traces .. rubric:: Example >>> from obspy import Trace, Stream >>> tr1 = Trace(data=np.array([0, -3, 9, 6, 4])) >>> tr2 = Trace(data=np.array([0, -3, -9, 6, 4])) >>> tr3 = Trace(data=np.array([0.3, -3.5, 9.0, 6.4, 4.3])) >>> st = Stream(traces=[tr1, tr2, tr3]) >>> st.max() [9, -9, 9.0] """ return [tr.max() for tr in self]
[docs] def differentiate(self, method='gradient'): """ Differentiate all traces with respect to time. :type method: str, optional :param method: Method to use for differentiation. Defaults to ``'gradient'``. See the `Supported Methods`_ section below for further details. .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. This also makes an entry with information on the applied processing in ``stats.processing`` of every trace. .. rubric:: _`Supported Methods` ``'gradient'`` The gradient is computed using central differences in the interior and first differences at the boundaries. The returned gradient hence has the same shape as the input array. (uses :func:`numpy.gradient`) """ for tr in self: tr.differentiate(method=method) return self
[docs] def integrate(self, method='cumtrapz', **options): """ Integrate all traces with respect to time. For details see the corresponding :meth:`~obspy.core.trace.Trace.integrate` method of :class:`~obspy.core.trace.Trace`. :type method: str, optional :param type: Method to use for integration. Defaults to ``'cumtrapz'``. See :meth:`~obspy.core.trace.Trace.integrate` for further details. .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. This also makes an entry with information on the applied processing in ``stats.processing`` of every trace. """ for tr in self: tr.integrate(method=method, **options) return self
@raise_if_masked
[docs] def detrend(self, type='simple', **options): """ Remove a trend from all traces. For details see the corresponding :meth:`~obspy.core.trace.Trace.detrend` method of :class:`~obspy.core.trace.Trace`. """ for tr in self: tr.detrend(type=type, **options) return self
[docs] def taper(self, *args, **kwargs): """ Taper all Traces in Stream. For details see the corresponding :meth:`~obspy.core.trace.Trace.taper` method of :class:`~obspy.core.trace.Trace`. .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. """ for tr in self: tr.taper(*args, **kwargs) return self
[docs] def interpolate(self, *args, **kwargs): """ Interpolate all Traces in a Stream. For details see the corresponding :meth:`~obspy.core.trace.Trace.interpolate` method of :class:`~obspy.core.trace.Trace`. .. note:: The :class:`~Stream` object has three different methods to change the sampling rate of its data: :meth:`~.resample`, :meth:`~.decimate`, and :meth:`~.interpolate` Make sure to choose the most appropriate one for the problem at hand. .. note:: This operation is performed in place on the actual data arrays. The raw data will no longer be accessible afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. >>> from obspy import read >>> st = read() >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03... - ... | 100.0 Hz, 3000 samples BW.RJOB..EHN | 2009-08-24T00:20:03... - ... | 100.0 Hz, 3000 samples BW.RJOB..EHE | 2009-08-24T00:20:03... - ... | 100.0 Hz, 3000 samples >>> st.interpolate(sampling_rate=111.1) # doctest: +ELLIPSIS <obspy.core.stream.Stream object at 0x...> >>> print(st) # doctest: +ELLIPSIS 3 Trace(s) in Stream: BW.RJOB..EHZ | 2009-08-24T00:20:03... - ... | 111.1 Hz, 3332 samples BW.RJOB..EHN | 2009-08-24T00:20:03... - ... | 111.1 Hz, 3332 samples BW.RJOB..EHE | 2009-08-24T00:20:03... - ... | 111.1 Hz, 3332 samples """ for tr in self: tr.interpolate(*args, **kwargs) return self
[docs] def std(self): """ Calculate standard deviations of all Traces in the Stream. Standard deviations are calculated by NumPy method :meth:`~numpy.ndarray.std` on ``trace.data`` for every trace in the stream. :return: List of standard deviations of all traces. .. rubric:: Example >>> from obspy import Trace, Stream >>> tr1 = Trace(data=np.array([0, -3, 9, 6, 4])) >>> tr2 = Trace(data=np.array([0.3, -3.5, 9.0, 6.4, 4.3])) >>> st = Stream(traces=[tr1, tr2]) >>> st.std() [4.2614551505325036, 4.4348618918744247] """ return [tr.std() for tr in self]
[docs] def normalize(self, global_max=False): """ Normalize all Traces in the Stream. By default all traces are normalized separately to their respective absolute maximum. By setting ``global_max=True`` all traces get normalized to the global maximum of all traces. :param global_max: If set to ``True``, all traces are normalized with respect to the global maximum of all traces in the stream instead of normalizing every trace separately. .. note:: If ``data.dtype`` of a trace was integer it is changing to float. .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. This also makes an entry with information on the applied processing in ``stats.processing`` of every trace. .. rubric:: Example Make a Stream with two Traces: >>> from obspy import Trace, Stream >>> tr1 = Trace(data=np.array([0, -3, 9, 6, 4])) >>> tr2 = Trace(data=np.array([0.3, -0.5, -0.8, 0.4, 0.3])) >>> st = Stream(traces=[tr1, tr2]) All traces are normalized to their absolute maximum and processing information is added: >>> st.normalize() # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st[0].data # doctest: +ELLIPSIS array([ 0. , -0.33333333, 1. , 0.66666667, ...]) >>> print(st[0].stats.processing[0]) # doctest: +ELLIPSIS ObsPy ... normalize(norm=None) >>> st[1].data array([ 0.375, -0.625, -1. , 0.5 , 0.375]) >>> print(st[1].stats.processing[0]) # doctest: +ELLIPSIS ObsPy ...: normalize(norm=None) Now let's do it again normalize all traces to the stream's global maximum: >>> tr1 = Trace(data=np.array([0, -3, 9, 6, 4])) >>> tr2 = Trace(data=np.array([0.3, -0.5, -0.8, 0.4, 0.3])) >>> st = Stream(traces=[tr1, tr2]) >>> st.normalize(global_max=True) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st[0].data # doctest: +ELLIPSIS array([ 0. , -0.33333333, 1. , 0.66666667, ...]) >>> print(st[0].stats.processing[0]) # doctest: +ELLIPSIS ObsPy ...: normalize(norm=9) >>> st[1].data # doctest: +ELLIPSIS array([ 0.03333333, -0.05555556, -0.08888889, 0.04444444, ...]) >>> print(st[1].stats.processing[0]) # doctest: +ELLIPSIS ObsPy ...: normalize(norm=9) """ # use the same value for normalization on all traces? if global_max: norm = max([abs(value) for value in self.max()]) else: norm = None # normalize all traces for tr in self: tr.normalize(norm=norm) return self
[docs] def rotate(self, method, back_azimuth=None, inclination=None): """ Rotate stream objects. :type method: str :param method: Determines the rotation method. ``'NE->RT'``: Rotates the North- and East-components of a seismogram to radial and transverse components. ``'RT->NE'``: Rotates the radial and transverse components of a seismogram to North- and East-components. ``'ZNE->LQT'``: Rotates from left-handed Z, North, and East system to LQT, e.g. right-handed ray coordinate system. ``'LQT->ZNE'``: Rotates from LQT, e.g. right-handed ray coordinate system to left handed Z, North, and East system. :type back_azimuth: float, optional :param back_azimuth: Depends on the chosen method. A single float, the back azimuth from station to source in degrees. If not given, ``stats.back_azimuth`` will be used. It will also be written after the rotation is done. :type inclination: float, optional :param inclination: Inclination of the ray at the station in degrees. Only necessary for three component rotations. If not given, ``stats.inclination`` will be used. It will also be written after the rotation is done. """ if method == "NE->RT": func = "rotate_ne_rt" elif method == "RT->NE": func = "rotate_rt_ne" elif method == "ZNE->LQT": func = "rotate_zne_lqt" elif method == "LQT->ZNE": func = "rotate_lqt_zne" else: raise ValueError("Method has to be one of ('NE->RT', 'RT->NE', " "'ZNE->LQT', or 'LQT->ZNE').") # Retrieve function call from entry points func = _get_function_from_entry_point("rotate", func) # Split to get the components. No need for further checks for the # method as invalid methods will be caught by previous conditional. input_components, output_components = method.split("->") # Figure out inclination and back-azimuth. if back_azimuth is None: try: back_azimuth = self[0].stats.back_azimuth except: msg = "No back-azimuth specified." raise TypeError(msg) if len(input_components) == 3 and inclination is None: try: inclination = self[0].stats.inclination except: msg = "No inclination specified." raise TypeError(msg) # Do one of the two-component rotations. if len(input_components) == 2: input_1 = self.select(component=input_components[0]) input_2 = self.select(component=input_components[1]) for i_1, i_2 in zip(input_1, input_2): dt = 0.5 * i_1.stats.delta if (len(i_1) != len(i_2)) or \ (abs(i_1.stats.starttime - i_2.stats.starttime) > dt) \ or (i_1.stats.sampling_rate != i_2.stats.sampling_rate): msg = "All components need to have the same time span." raise ValueError(msg) for i_1, i_2 in zip(input_1, input_2): output_1, output_2 = func(i_1.data, i_2.data, back_azimuth) i_1.data = output_1 i_2.data = output_2 # Rename the components. i_1.stats.channel = i_1.stats.channel[:-1] + \ output_components[0] i_2.stats.channel = i_2.stats.channel[:-1] + \ output_components[1] # Add the azimuth and inclination to the stats object. for comp in (i_1, i_2): comp.stats.back_azimuth = back_azimuth # Do one of the three-component rotations. else: input_1 = self.select(component=input_components[0]) input_2 = self.select(component=input_components[1]) input_3 = self.select(component=input_components[2]) for i_1, i_2, i_3 in zip(input_1, input_2, input_3): dt = 0.5 * i_1.stats.delta if (len(i_1) != len(i_2)) or (len(i_1) != len(i_3)) or \ (abs(i_1.stats.starttime - i_2.stats.starttime) > dt) or \ (abs(i_1.stats.starttime - i_3.stats.starttime) > dt) or \ (i_1.stats.sampling_rate != i_2.stats.sampling_rate) or \ (i_1.stats.sampling_rate != i_3.stats.sampling_rate): msg = "All components need to have the same time span." raise ValueError(msg) for i_1, i_2, i_3 in zip(input_1, input_2, input_3): output_1, output_2, output_3 = func( i_1.data, i_2.data, i_3.data, back_azimuth, inclination) i_1.data = output_1 i_2.data = output_2 i_3.data = output_3 # Rename the components. i_1.stats.channel = i_1.stats.channel[:-1] + \ output_components[0] i_2.stats.channel = i_2.stats.channel[:-1] + \ output_components[1] i_3.stats.channel = i_3.stats.channel[:-1] + \ output_components[2] # Add the azimuth and inclination to the stats object. for comp in (i_1, i_2, i_3): comp.stats.back_azimuth = back_azimuth comp.stats.inclination = inclination return self
[docs] def copy(self): """ Return a deepcopy of the Stream object. :rtype: :class:`~obspy.core.stream.Stream` :return: Copy of current stream. .. rubric:: Examples 1. Create a Stream and copy it >>> from obspy import read >>> st = read() >>> st2 = st.copy() The two objects are not the same: >>> st is st2 False But they have equal data (before applying further processing): >>> st == st2 True 2. The following example shows how to make an alias but not copy the data. Any changes on ``st3`` would also change the contents of ``st``. >>> st3 = st >>> st is st3 True >>> st == st3 True """ return copy.deepcopy(self)
[docs] def clear(self): """ Clear trace list (convenience method). Replaces Stream's trace list by an empty one creating an empty Stream object. Useful if there are references to the current Stream object that should not break. Otherwise simply use a new Stream() instance. .. rubric:: Example >>> from obspy import read >>> st = read() >>> len(st) 3 >>> st.clear() # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st.traces [] """ self.traces = [] return self
[docs] def _cleanup(self, misalignment_threshold=1e-2): """ Merge consistent trace objects but leave everything else alone. This can mean traces with matching header that are directly adjacent or are contained/equal/overlapping traces with exactly the same waveform data in the overlapping part. If option `misalignment_threshold` is non-zero then contained/overlapping/directly adjacent traces with the sampling points misaligned by less than `misalignment_threshold` times the sampling interval are aligned on the same sampling points (see example below). .. rubric:: Notes Traces with overlapping data parts that do not match are not merged:: before: Trace 1: AAAAAAAA Trace 2: BBBBBBBB after: Trace 1: AAAAAAAA Trace 2: BBBBBBBB Traces with overlapping data parts that do match are merged:: before: Trace 1: AAAAAAAA Trace 2: AAAABBBB after: Trace 1: AAAAAAAABBBB Contained traces are handled the same way. If common data does not match, nothing is done:: before: Trace 1: AAAAAAAAAAAA Trace 2: BBBB after: Trace 1: AAAAAAAAAAAA Trace 2: BBBB If the common data part matches they are merged:: before: Trace 1: AAAAAAAAAAAA Trace 2: AAAA after: Trace 1: AAAAAAAAAAAA Directly adjacent traces are merged:: before: Trace 1: AAAAAAA Trace 2: BBBBB after: Trace 1: AAAAAAABBBBB Misaligned traces are aligned, depending on set parameters, e.g. for a directly adjacent trace with slight misalignment (with two common samples at start of Trace 2 for better visualization):: before: Trace 1: A---------A---------A Trace 2: A---------A---------B---------B after: Trace 1: A---------A---------A---------B---------B :type misalignment_threshold: float :param misalignment_threshold: Threshold value for sub-sample misalignments of sampling points of two traces that should be merged together (fraction of sampling interval, from 0 to 0.5). ``0`` means traces with even just the slightest misalignment will not be merged together, ``0.5`` means traces will be merged together disregarding of any sub-sample shifts of sampling points. """ # first of all throw away all empty traces self.traces = [_i for _i in self.traces if _i.stats.npts] # check sampling rates and dtypes try: self._merge_checks() except Exception as e: if "Can't merge traces with same ids but" in str(e): msg = "Incompatible traces (sampling_rate, dtype, ...) " + \ "with same id detected. Doing nothing." warnings.warn(msg) return # order matters! self.sort(keys=['network', 'station', 'location', 'channel', 'starttime', 'endtime']) # build up dictionary with lists of traces with same ids traces_dict = {} # using pop() and try-except saves memory try: while True: trace = self.traces.pop(0) # add trace to respective list or create that list traces_dict.setdefault(trace.id, []).append(trace) except IndexError: pass # clear traces of current stream self.traces = [] # loop through ids for id_ in traces_dict.keys(): trace_list = traces_dict[id_] cur_trace = trace_list.pop(0) delta = cur_trace.stats.delta allowed_micro_shift = misalignment_threshold * delta # work through all traces of same id while trace_list: trace = trace_list.pop(0) # `gap` is the deviation (in seconds) of the actual start # time of the second trace from the expected start time # (for the ideal case of directly adjacent and perfectly # aligned traces). gap = trace.stats.starttime - (cur_trace.stats.endtime + delta) # if `gap` is larger than the designated allowed shift, # we treat it as a real gap and leave as is. if misalignment_threshold > 0 and gap <= allowed_micro_shift: # `gap` is smaller than allowed shift (or equal), # the traces could be # - overlapping without being misaligned or.. # - overlapping with misalignment or.. # - misaligned with a micro gap # check if the sampling points are misaligned: misalignment = gap % delta if misalignment != 0: # determine the position of the second trace's # sampling points in the interval between two # sampling points of first trace. # a `misalign_percentage` of close to 0.0 means a # sampling point of the first trace is just a bit # to the left of our sampling point: # # Trace 1: --|---------|---------|---------|-- # Trace 2: ---|---------|---------|---------|- # misalign_percentage: 0.........1 # # a `misalign_percentage` of close to 1.0 means a # sampling point of the first trace is just a bit # to the right of our sampling point: # # Trace 1: --|---------|---------|---------|-- # Trace 2: -|---------|---------|---------|--- # misalign_percentage: 0.........1 misalign_percentage = misalignment / delta if (misalign_percentage <= misalignment_threshold or misalign_percentage >= 1 - misalignment_threshold): # now we align the sampling points of both traces trace.stats.starttime = ( cur_trace.stats.starttime + round((trace.stats.starttime - cur_trace.stats.starttime) / delta) * delta) # we have some common parts: check if consistent # (but only if sampling points are matching to specified # accuracy, which is checked and conditionally corrected in # previous code block) subsample_shift_percentage = ( trace.stats.starttime.timestamp - cur_trace.stats.starttime.timestamp) % delta / delta subsample_shift_percentage = min( subsample_shift_percentage, 1 - subsample_shift_percentage) if (trace.stats.starttime <= cur_trace.stats.endtime and subsample_shift_percentage < misalignment_threshold): # check if common time slice [t1 --> t2] is equal: t1 = trace.stats.starttime t2 = min(cur_trace.stats.endtime, trace.stats.endtime) # if consistent: add them together if np.array_equal(cur_trace.slice(t1, t2).data, trace.slice(t1, t2).data): cur_trace += trace # if not consistent: leave them alone else: self.traces.append(cur_trace) cur_trace = trace # traces are perfectly adjacent: add them together elif trace.stats.starttime == cur_trace.stats.endtime + \ cur_trace.stats.delta: cur_trace += trace # no common parts (gap): # leave traces alone and add current to list else: self.traces.append(cur_trace) cur_trace = trace self.traces.append(cur_trace) self.traces = [tr for tr in self.traces if tr.stats.npts] return self
[docs] def split(self): """ Split any trace containing gaps into contiguous unmasked traces. :rtype: :class:`obspy.core.stream.Stream` :returns: Returns a new stream object containing only contiguous unmasked. """ new_stream = Stream() for trace in self.traces: new_stream.extend(trace.split()) return new_stream
@map_example_filename("inventories")
[docs] def attach_response(self, inventories): """ Search for and attach channel response to each trace as trace.stats.response. Does not raise an exception but shows a warning if response information can not be found for all traces. Returns a list of traces for which no response could be found. To subsequently deconvolve the instrument response use :meth:`Stream.remove_response`. >>> from obspy import read, read_inventory >>> st = read() >>> inv = read_inventory() >>> st.attach_response(inv) [] >>> tr = st[0] >>> print(tr.stats.response) \ # doctest: +ELLIPSIS +NORMALIZE_WHITESPACE Channel Response From M/S (Velocity in Meters per Second) to COUNTS (Digital Counts) Overall Sensitivity: 2.5168e+09 defined at 0.020 Hz 4 stages: Stage 1: PolesZerosResponseStage from M/S to V, gain: 1500 Stage 2: CoefficientsTypeResponseStage from V to COUNTS, ... Stage 3: FIRResponseStage from COUNTS to COUNTS, gain: 1 Stage 4: FIRResponseStage from COUNTS to COUNTS, gain: 1 :type inventories: :class:`~obspy.core.inventory.inventory.Inventory` or :class:`~obspy.core.inventory.network.Network` or a list containing objects of these types. :param inventories: Station metadata to use in search for response for each trace in the stream. :rtype: list of :class:`~obspy.core.trace.Trace` :returns: list of traces for which no response information could be found. """ skipped_traces = [] for tr in self.traces: try: tr.attach_response(inventories) except Exception as e: if str(e) == "No matching response information found.": warnings.warn(str(e)) skipped_traces.append(tr) else: raise return skipped_traces
[docs] def remove_response(self, *args, **kwargs): """ Deconvolve instrument response for all Traces in Stream. For details see the corresponding :meth:`~obspy.core.trace.Trace.remove_response` method of :class:`~obspy.core.trace.Trace`. >>> from obspy import read, read_inventory >>> st = read() >>> inv = read_inventory() >>> st.remove_response(inventory=inv) # doctest: +ELLIPSIS <...Stream object at 0x...> >>> st.plot() # doctest: +SKIP .. plot:: from obspy import read, read_inventory st = read() inv = read_inventory() st.remove_response(inventory=inv) st.plot() .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. """ for tr in self: tr.remove_response(*args, **kwargs) return self
[docs] def remove_sensitivity(self, *args, **kwargs): """ Remove instrument sensitivity for all Traces in Stream. For details see the corresponding :meth:`~obspy.core.trace.Trace.remove_sensitivity` method of :class:`~obspy.core.trace.Trace`. >>> from obspy import read, read_inventory >>> st = read() >>> inv = read_inventory() >>> st.remove_sensitivity(inv) # doctest: +ELLIPSIS <...Stream object at 0x...> .. note:: This operation is performed in place on the actual data arrays. The raw data is not accessible anymore afterwards. To keep your original data, use :meth:`~obspy.core.stream.Stream.copy` to create a copy of your stream object. """ for tr in self: tr.remove_sensitivity(*args, **kwargs) return self
@deprecated("Renamed to '_is_pickle'. Use that instead.")
[docs]def isPickle(*args, **kwargs): # noqa return _is_pickle(*args, **kwargs)
@deprecated("Renamed to '_read_pickle'. Use that instead.")
[docs]def readPickle(*args, **kwargs): # noqa return _read_pickle(*args, **kwargs)
@deprecated("Renamed to '_write_pickle'. Use that instead.")
[docs]def writePickle(*args, **kwargs): # noqa return _write_pickle(*args, **kwargs)
[docs]def _is_pickle(filename): # @UnusedVariable """ Check whether a file is a pickled ObsPy Stream file. :type filename: str :param filename: Name of the pickled ObsPy Stream file to be checked. :rtype: bool :return: ``True`` if pickled file. .. rubric:: Example >>> _is_pickle('/path/to/pickle.file') # doctest: +SKIP True """ if isinstance(filename, (str, native_str)): try: with open(filename, 'rb') as fp: st = pickle.load(fp) except: return False else: try: st = pickle.load(filename) except: return False return isinstance(st, Stream)
[docs]def _read_pickle(filename, **kwargs): # @UnusedVariable """ Read and return Stream from pickled ObsPy Stream file. .. warning:: This function should NOT be called directly, it registers via the ObsPy :func:`~obspy.core.stream.read` function, call this instead. :type filename: str :param filename: Name of the pickled ObsPy Stream file to be read. :rtype: :class:`~obspy.core.stream.Stream` :return: A ObsPy Stream object. """ if isinstance(filename, (str, native_str)): with open(filename, 'rb') as fp: return pickle.load(fp) else: return pickle.load(filename)
[docs]def _write_pickle(stream, filename, protocol=2, **kwargs): # @UnusedVariable """ Write a Python pickle of current stream. .. note:: Writing into PICKLE format allows to store additional attributes appended to the current Stream object or any contained Trace. .. warning:: This function should NOT be called directly, it registers via the the :meth:`~obspy.core.stream.Stream.write` method of an ObsPy :class:`~obspy.core.stream.Stream` object, call this instead. :type stream: :class:`~obspy.core.stream.Stream` :param stream: The ObsPy Stream object to write. :type filename: str :param filename: Name of file to write. :type protocol: int, optional :param protocol: Pickle protocol, defaults to ``2``. """ if isinstance(filename, (str, native_str)): with open(filename, 'wb') as fp: pickle.dump(stream, fp, protocol=protocol) else: pickle.dump(stream, filename, protocol=protocol)
if __name__ == '__main__': import doctest doctest.testmod(exclude_empty=True)