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test_trace.py
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test_trace.py
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# -*- coding: utf-8 -*-
from copy import deepcopy
import numpy as np
from obspy import Trace, UTCDateTime, read
from obspy.signal.filter import (bandpass, bandstop, highpass, lowpass,
lowpass_cheby_2)
from obspy.signal.invsim import simulate_seismometer
import pytest
class TestTrace():
"""
Test suite for obspy.core.trace.Trace.
"""
def test_simulate(self):
"""
Tests if calling simulate of trace gives the same result as using
simulate_seismometer manually.
"""
tr = read()[0]
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_le3d1s = {'poles': [-4.440 + 4.440j, -4.440 - 4.440j,
- 1.083 + 0.0j],
'zeros': [0.0 + 0.0j, 0.0 + 0.0j, 0.0 + 0.0j],
'gain': 0.4,
'sensitivity': 1.0}
data = simulate_seismometer(
tr.data, tr.stats.sampling_rate, paz_remove=paz_sts2,
paz_simulate=paz_le3d1s, remove_sensitivity=True,
simulate_sensitivity=True)
tr.simulate(paz_remove=paz_sts2, paz_simulate=paz_le3d1s)
# There is some strange issue on Win32bit (see #2188). Thus we just
# use assert_allclose() here instead of testing for full equality.
np.testing.assert_allclose(tr.data, data)
def test_filter(self):
"""
Tests the filter method of the Trace object.
Basically three scenarios are tested (with differing filter options):
- filtering with in_place=False:
- is original trace unchanged?
- is data of filtered trace the same as if done by hand
- is processing information present in filtered trace
- filtering with in_place=True:
- is data of filtered trace the same as if done by hand
- is processing information present in filtered trace
- filtering with bad arguments passed to trace.filter():
- is a TypeError properly raised?
- after all bad filter calls, is the trace still unchanged?
"""
# create two test Traces
traces = []
np.random.seed(815)
header = {'network': 'BW', 'station': 'BGLD',
'starttime': UTCDateTime(2007, 12, 31, 23, 59, 59, 915000),
'npts': 412, 'sampling_rate': 200.0,
'channel': 'EHE'}
traces.append(Trace(data=np.random.randint(0, 1000, 412),
header=deepcopy(header)))
header['starttime'] = UTCDateTime(2008, 1, 1, 0, 0, 4, 35000)
header['npts'] = 824
traces.append(Trace(data=np.random.randint(0, 1000, 824),
header=deepcopy(header)))
traces_bkp = deepcopy(traces)
# different sets of filters to run test on:
filters = [['bandpass', {'freqmin': 1., 'freqmax': 20.}],
['bandstop', {'freqmin': 5, 'freqmax': 15., 'corners': 6}],
['lowpass', {'freq': 30.5, 'zerophase': True}],
['highpass', {'freq': 2, 'corners': 2}]]
filter_map = {'bandpass': bandpass, 'bandstop': bandstop,
'lowpass': lowpass, 'highpass': highpass}
# tests for in_place=True
for i, tr in enumerate(traces):
for filt_type, filt_ops in filters:
tr = deepcopy(traces_bkp[i])
tr.filter(filt_type, **filt_ops)
# test if trace was filtered as expected
data_filt = filter_map[filt_type](
traces_bkp[i].data,
df=traces_bkp[i].stats.sampling_rate, **filt_ops)
np.testing.assert_array_equal(tr.data, data_filt)
assert 'processing' in tr.stats
assert len(tr.stats.processing) == 1
assert "filter" in tr.stats.processing[0]
assert filt_type in tr.stats.processing[0]
for key, value in filt_ops.items():
assert "'%s': %s" % (key, value) \
in tr.stats.processing[0]
# another filter run
tr.filter(filt_type, **filt_ops)
data_filt = filter_map[filt_type](
data_filt,
df=traces_bkp[i].stats.sampling_rate, **filt_ops)
np.testing.assert_array_equal(tr.data, data_filt)
assert 'processing' in tr.stats
assert len(tr.stats.processing) == 2
for proc_info in tr.stats.processing:
assert "filter" in proc_info
assert filt_type in proc_info
for key, value in filt_ops.items():
assert "'%s': %s" % (key, value) \
in proc_info
# some tests that should raise an Exception
tr = traces[0]
bad_filters = [
['bandpass', {'freqmin': 1., 'XXX': 20.}],
['bandstop', {'freqmin': 5, 'freqmax': "XXX", 'corners': 6}],
['bandstop', {}],
['bandstop', [1, 2, 3, 4, 5]],
['bandstop', None],
['bandstop', 3],
['bandstop', 'XXX'],
['bandpass', {'freqmin': 5, 'corners': 6}],
['bandpass', {'freqmin': 5, 'freqmax': 20., 'df': 100.}]]
for filt_type, filt_ops in bad_filters:
with pytest.raises(TypeError):
tr.filter(filt_type, filt_ops)
bad_filters = [['XXX', {'freqmin': 5, 'freqmax': 20., 'corners': 6}]]
for filt_type, filt_ops in bad_filters:
with pytest.raises(ValueError):
tr.filter(filt_type, **filt_ops)
# test if trace is unchanged after all these bad tests
np.testing.assert_array_equal(tr.data, traces_bkp[0].data)
assert tr.stats == traces_bkp[0].stats
def test_decimate(self):
"""
Tests the decimate method of the Trace object.
"""
# create test Trace
tr = Trace(data=np.arange(20))
tr_bkp = deepcopy(tr)
# some test that should fail and leave the original trace alone
with pytest.raises(ValueError):
tr.decimate(7, strict_length=True)
with pytest.raises(ValueError):
tr.decimate(9, strict_length=True)
with pytest.raises(ArithmeticError):
tr.decimate(18)
# some tests in place
tr.decimate(4, no_filter=True)
np.testing.assert_array_equal(tr.data, np.arange(0, 20, 4))
assert tr.stats.npts == 5
assert tr.stats.sampling_rate == 0.25
assert "decimate" in tr.stats.processing[0]
assert "factor=4" in tr.stats.processing[0]
tr = tr_bkp.copy()
tr.decimate(10, no_filter=True)
np.testing.assert_array_equal(tr.data, np.arange(0, 20, 10))
assert tr.stats.npts == 2
assert tr.stats.sampling_rate == 0.1
assert "decimate" in tr.stats.processing[0]
assert "factor=10" in tr.stats.processing[0]
# some tests with automatic prefiltering
tr = tr_bkp.copy()
tr2 = tr_bkp.copy()
tr.decimate(4)
df = tr2.stats.sampling_rate
tr2.data, fp = lowpass_cheby_2(data=tr2.data, freq=df * 0.5 / 4.0,
df=df, maxorder=12, ba=False,
freq_passband=True)
# check that iteratively determined pass band frequency is correct
assert round(abs(0.0811378285461-fp), 7) == 0
tr2.decimate(4, no_filter=True)
np.testing.assert_array_equal(tr.data, tr2.data)