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test_trigger.py
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test_trigger.py
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# -*- coding: utf-8 -*-
"""
The obspy.signal.trigger test suite.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from future.builtins import * # NOQA
import gzip
import os
import unittest
import warnings
from ctypes import ArgumentError
import numpy as np
from obspy import Stream, UTCDateTime, read
from obspy.signal.trigger import (
ar_pick, classic_sta_lta, classic_sta_lta_py, coincidence_trigger, pk_baer,
recursive_sta_lta, recursive_sta_lta_py, trigger_onset)
from obspy.signal.util import clibsignal
class TriggerTestCase(unittest.TestCase):
"""
Test cases for obspy.trigger
"""
def setUp(self):
# directory where the test files are located
self.path = os.path.join(os.path.dirname(__file__), 'data')
# random seed data
np.random.seed(815)
self.data = np.random.randn(int(1e5))
def test_rec_sta_lta_c(self):
"""
Test case for ctypes version of recursive_sta_lta
"""
nsta, nlta = 5, 10
c1 = recursive_sta_lta(self.data, nsta, nlta)
self.assertAlmostEqual(c1[99], 0.80810165)
self.assertAlmostEqual(c1[100], 0.75939449)
self.assertAlmostEqual(c1[101], 0.91763978)
self.assertAlmostEqual(c1[102], 0.97465004)
def test_rec_sta_lta_python(self):
"""
Test case for python version of recursive_sta_lta
"""
nsta, nlta = 5, 10
c2 = recursive_sta_lta_py(self.data, nsta, nlta)
self.assertAlmostEqual(c2[99], 0.80810165)
self.assertAlmostEqual(c2[100], 0.75939449)
self.assertAlmostEqual(c2[101], 0.91763978)
self.assertAlmostEqual(c2[102], 0.97465004)
def test_rec_sta_lta_raise(self):
"""
Type checking recursive_sta_lta
"""
ndat = 1
charfct = np.empty(ndat, dtype=np.float64)
self.assertRaises(ArgumentError, clibsignal.recstalta, [1], charfct,
ndat, 5, 10)
self.assertRaises(ArgumentError, clibsignal.recstalta,
np.array([1], dtype=np.int32), charfct, ndat, 5, 10)
def test_pk_baer(self):
"""
Test pk_baer against implementation for UNESCO short course
"""
filename = os.path.join(self.path, 'manz_waldk.a01.gz')
with gzip.open(filename) as f:
data = np.loadtxt(f, dtype=np.float32)
df, ntdownmax, ntupevent, thr1, thr2, npreset_len, np_dur = \
(200.0, 20, 60, 7.0, 12.0, 100, 100)
nptime, pfm = pk_baer(data, df, ntdownmax, ntupevent,
thr1, thr2, npreset_len, np_dur)
self.assertEqual(nptime, 17545)
self.assertEqual(pfm, 'IPU0')
def test_pk_baer_cf(self):
"""
Test pk_baer against implementation for UNESCO short course
"""
filename = os.path.join(self.path, 'manz_waldk.a01.gz')
with gzip.open(filename) as f:
data = np.loadtxt(f, dtype=np.float32)
df, ntdownmax, ntupevent, thr1, thr2, npreset_len, np_dur = \
(200.0, 20, 60, 7.0, 12.0, 100, 100)
nptime, pfm, cf = pk_baer(data, df, ntdownmax, ntupevent,
thr1, thr2, npreset_len, np_dur,
return_cf=True)
self.assertEqual(nptime, 17545)
self.assertEqual(pfm, 'IPU0')
self.assertEqual(len(cf), 119999)
def test_ar_pick(self):
"""
Test ar_pick against implementation for UNESCO short course
"""
data = []
for channel in ['z', 'n', 'e']:
file = os.path.join(self.path,
'loc_RJOB20050801145719850.' + channel)
data.append(np.loadtxt(file, dtype=np.float32))
# some default arguments
samp_rate, f1, f2, lta_p, sta_p, lta_s, sta_s, m_p, m_s, l_p, l_s = \
200.0, 1.0, 20.0, 1.0, 0.1, 4.0, 1.0, 2, 8, 0.1, 0.2
ptime, stime = ar_pick(data[0], data[1], data[2], samp_rate, f1, f2,
lta_p, sta_p, lta_s, sta_s, m_p, m_s, l_p, l_s)
self.assertAlmostEqual(ptime, 30.6350002289)
# seems to be strongly machine dependent, go for int for 64 bit
# self.assertEqual(int(stime + 0.5), 31)
self.assertAlmostEqual(stime, 31.165, delta=0.05)
# All three arrays must have the same length, otherwise an error is
# raised.
with self.assertRaises(ValueError) as err:
ar_pick(data[0], data[1], np.zeros(1), samp_rate, f1, f2, lta_p,
sta_p, lta_s, sta_s, m_p, m_s, l_p, l_s)
self.assertEqual(err.exception.args[0],
"All three data arrays must have the same length.")
def test_ar_pick_low_amplitude(self):
"""
Test ar_pick with low amplitude data
"""
data = []
for channel in ['z', 'n', 'e']:
file = os.path.join(self.path,
'loc_RJOB20050801145719850.' + channel)
data.append(np.loadtxt(file, dtype=np.float32))
# articially reduce signal amplitude
for d in data:
d /= 10.0 * d.max()
# some default arguments
samp_rate, f1, f2, lta_p, sta_p, lta_s, sta_s, m_p, m_s, l_p, l_s = \
200.0, 1.0, 20.0, 1.0, 0.1, 4.0, 1.0, 2, 8, 0.1, 0.2
ptime, stime = ar_pick(data[0], data[1], data[2], samp_rate, f1, f2,
lta_p, sta_p, lta_s, sta_s, m_p, m_s, l_p, l_s)
self.assertAlmostEqual(ptime, 30.6350002289)
# seems to be strongly machine dependent, go for int for 64 bit
# self.assertAlmostEqual(stime, 31.2800006866)
self.assertEqual(int(stime + 0.5), 31)
def test_trigger_onset(self):
"""
Test trigger onset function
"""
on_of = np.array([[6.0, 31], [69, 94], [131, 181], [215, 265],
[278, 315], [480, 505], [543, 568], [605, 631]])
cft = np.concatenate((np.sin(np.arange(0, 5 * np.pi, 0.1)) + 1,
np.sin(np.arange(0, 5 * np.pi, 0.1)) + 2.1,
np.sin(np.arange(0, 5 * np.pi, 0.1)) + 0.4,
np.sin(np.arange(0, 5 * np.pi, 0.1)) + 1))
picks = trigger_onset(cft, 1.5, 1.0, max_len=50)
np.testing.assert_array_equal(picks, on_of)
# check that max_len_delete drops the picks
picks_del = trigger_onset(cft, 1.5, 1.0, max_len=50,
max_len_delete=True)
np.testing.assert_array_equal(
picks_del, on_of[np.array([0, 1, 5, 6, 7])])
#
# set True for visual understanding the tests
if False: # pragma: no cover
import matplotlib.pyplot as plt
plt.plot(cft)
plt.hlines([1.5, 1.0], 0, len(cft))
on_of = np.array(on_of)
plt.vlines(picks[:, 0], 1.0, 2.0, color='g', linewidth=2,
label="ON max_len")
plt.vlines(picks[:, 1], 0.5, 1.5, color='r', linewidth=2,
label="OF max_len")
plt.vlines(picks_del[:, 0] + 2, 1.0, 2.0, color='y', linewidth=2,
label="ON max_len_delete")
plt.vlines(picks_del[:, 1] + 2, 0.5, 1.5, color='b', linewidth=2,
label="OF max_len_delete")
plt.legend()
plt.show()
def test_coincidence_trigger(self):
"""
Test network coincidence trigger.
"""
st = Stream()
files = ["BW.UH1._.SHZ.D.2010.147.cut.slist.gz",
"BW.UH2._.SHZ.D.2010.147.cut.slist.gz",
"BW.UH3._.SHZ.D.2010.147.cut.slist.gz",
"BW.UH4._.EHZ.D.2010.147.cut.slist.gz"]
for filename in files:
filename = os.path.join(self.path, filename)
st += read(filename)
# some prefiltering used for UH network
st.filter('bandpass', freqmin=10, freqmax=20)
# 1. no weighting, no stations specified, good settings
# => 3 events, no false triggers
# for the first test we make some additional tests regarding types
res = coincidence_trigger("recstalta", 3.5, 1, st.copy(), 3, sta=0.5,
lta=10)
self.assertTrue(isinstance(res, list))
self.assertEqual(len(res), 3)
expected_keys = ['time', 'coincidence_sum', 'duration', 'stations',
'trace_ids']
expected_types = [UTCDateTime, float, float, list, list]
for item in res:
self.assertTrue(isinstance(item, dict))
for key, _type in zip(expected_keys, expected_types):
self.assertIn(key, item)
self.assertTrue(isinstance(item[key], _type))
self.assertGreater(res[0]['time'], UTCDateTime("2010-05-27T16:24:31"))
self.assertTrue(res[0]['time'] < UTCDateTime("2010-05-27T16:24:35"))
self.assertTrue(4.2 < res[0]['duration'] < 4.8)
self.assertEqual(res[0]['stations'], ['UH3', 'UH2', 'UH1', 'UH4'])
self.assertEqual(res[0]['coincidence_sum'], 4)
self.assertGreater(res[1]['time'], UTCDateTime("2010-05-27T16:26:59"))
self.assertTrue(res[1]['time'] < UTCDateTime("2010-05-27T16:27:03"))
self.assertTrue(3.2 < res[1]['duration'] < 3.7)
self.assertEqual(res[1]['stations'], ['UH2', 'UH3', 'UH1'])
self.assertEqual(res[1]['coincidence_sum'], 3)
self.assertGreater(res[2]['time'], UTCDateTime("2010-05-27T16:27:27"))
self.assertTrue(res[2]['time'] < UTCDateTime("2010-05-27T16:27:33"))
self.assertTrue(4.2 < res[2]['duration'] < 4.4)
self.assertEqual(res[2]['stations'], ['UH3', 'UH2', 'UH1', 'UH4'])
self.assertEqual(res[2]['coincidence_sum'], 4)
# 2. no weighting, station selection
# => 2 events, no false triggers
trace_ids = ['BW.UH1..SHZ', 'BW.UH3..SHZ', 'BW.UH4..EHZ']
# raises "UserWarning: At least one trace's ID was not found"
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always', UserWarning)
re = coincidence_trigger("recstalta", 3.5, 1, st.copy(), 3,
trace_ids=trace_ids, sta=0.5, lta=10)
self.assertEqual(len(w), 1)
self.assertIn("At least one trace's ID was not", str(w[0]))
self.assertEqual(len(re), 2)
self.assertGreater(re[0]['time'],
UTCDateTime("2010-05-27T16:24:31"))
self.assertTrue(re[0]['time'] < UTCDateTime("2010-05-27T16:24:35"))
self.assertTrue(4.2 < re[0]['duration'] < 4.8)
self.assertEqual(re[0]['stations'], ['UH3', 'UH1', 'UH4'])
self.assertEqual(re[0]['coincidence_sum'], 3)
self.assertGreater(re[1]['time'],
UTCDateTime("2010-05-27T16:27:27"))
self.assertTrue(re[1]['time'] < UTCDateTime("2010-05-27T16:27:33"))
self.assertTrue(4.2 < re[1]['duration'] < 4.4)
self.assertEqual(re[1]['stations'], ['UH3', 'UH1', 'UH4'])
self.assertEqual(re[1]['coincidence_sum'], 3)
# 3. weighting, station selection
# => 3 events, no false triggers
trace_ids = {'BW.UH1..SHZ': 0.4, 'BW.UH2..SHZ': 0.35,
'BW.UH3..SHZ': 0.4, 'BW.UH4..EHZ': 0.25}
res = coincidence_trigger("recstalta", 3.5, 1, st.copy(), 1.0,
trace_ids=trace_ids, sta=0.5, lta=10)
self.assertEqual(len(res), 3)
self.assertGreater(res[0]['time'], UTCDateTime("2010-05-27T16:24:31"))
self.assertTrue(res[0]['time'] < UTCDateTime("2010-05-27T16:24:35"))
self.assertTrue(4.2 < res[0]['duration'] < 4.8)
self.assertEqual(res[0]['stations'], ['UH3', 'UH2', 'UH1', 'UH4'])
self.assertEqual(res[0]['coincidence_sum'], 1.4)
self.assertGreater(res[1]['time'], UTCDateTime("2010-05-27T16:26:59"))
self.assertTrue(res[1]['time'] < UTCDateTime("2010-05-27T16:27:03"))
self.assertTrue(3.2 < res[1]['duration'] < 3.7)
self.assertEqual(res[1]['stations'], ['UH2', 'UH3', 'UH1'])
self.assertEqual(res[1]['coincidence_sum'], 1.15)
self.assertGreater(res[2]['time'], UTCDateTime("2010-05-27T16:27:27"))
self.assertTrue(res[2]['time'] < UTCDateTime("2010-05-27T16:27:33"))
self.assertTrue(4.2 < res[2]['duration'] < 4.4)
self.assertEqual(res[2]['stations'], ['UH3', 'UH2', 'UH1', 'UH4'])
self.assertEqual(res[2]['coincidence_sum'], 1.4)
# 4. weighting, station selection, max_len
# => 2 events, no false triggers, small event does not overlap anymore
trace_ids = {'BW.UH1..SHZ': 0.6, 'BW.UH2..SHZ': 0.6}
# raises "UserWarning: At least one trace's ID was not found"
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always', UserWarning)
re = coincidence_trigger("recstalta", 3.5, 1, st.copy(), 1.2,
trace_ids=trace_ids,
max_trigger_length=0.13, sta=0.5, lta=10)
self.assertEqual(len(w), 2)
self.assertIn("At least one trace's ID was not", str(w[0]))
self.assertIn("At least one trace's ID was not", str(w[1]))
self.assertEqual(len(re), 2)
self.assertGreater(re[0]['time'],
UTCDateTime("2010-05-27T16:24:31"))
self.assertTrue(re[0]['time'] < UTCDateTime("2010-05-27T16:24:35"))
self.assertTrue(0.2 < re[0]['duration'] < 0.3)
self.assertEqual(re[0]['stations'], ['UH2', 'UH1'])
self.assertEqual(re[0]['coincidence_sum'], 1.2)
self.assertGreater(re[1]['time'],
UTCDateTime("2010-05-27T16:27:27"))
self.assertTrue(re[1]['time'] < UTCDateTime("2010-05-27T16:27:33"))
self.assertTrue(0.18 < re[1]['duration'] < 0.2)
self.assertEqual(re[1]['stations'], ['UH2', 'UH1'])
self.assertEqual(re[1]['coincidence_sum'], 1.2)
# 5. station selection, extremely sensitive settings
# => 4 events, 1 false triggers
# raises "UserWarning: At least one trace's ID was not found"
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always', UserWarning)
res = coincidence_trigger("recstalta", 2.5, 1, st.copy(), 2,
trace_ids=['BW.UH1..SHZ', 'BW.UH3..SHZ'],
sta=0.3, lta=5)
self.assertEqual(len(w), 2)
self.assertIn("At least one trace's ID was not", str(w[0]))
self.assertIn("At least one trace's ID was not", str(w[1]))
self.assertEqual(len(res), 5)
self.assertGreater(res[3]['time'], UTCDateTime("2010-05-27T16:27:01"))
self.assertTrue(res[3]['time'] < UTCDateTime("2010-05-27T16:27:02"))
self.assertTrue(1.5 < res[3]['duration'] < 1.7)
self.assertEqual(res[3]['stations'], ['UH3', 'UH1'])
self.assertEqual(res[3]['coincidence_sum'], 2.0)
# 6. same as 5, gappy stream
# => same as 5 (almost, duration of 1 event changes by 0.02s)
st2 = st.copy()
tr1 = st2.pop(0)
t1 = tr1.stats.starttime
t2 = tr1.stats.endtime
td = t2 - t1
tr1a = tr1.slice(starttime=t1, endtime=t1 + 0.45 * td)
tr1b = tr1.slice(starttime=t1 + 0.6 * td, endtime=t1 + 0.94 * td)
st2.insert(1, tr1a)
st2.insert(3, tr1b)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always', UserWarning)
res = coincidence_trigger("recstalta", 2.5, 1, st2, 2,
trace_ids=['BW.UH1..SHZ', 'BW.UH3..SHZ'],
sta=0.3, lta=5)
self.assertEqual(len(w), 2)
self.assertIn("At least one trace's ID was not", str(w[0]))
self.assertIn("At least one trace's ID was not", str(w[1]))
self.assertEqual(len(res), 5)
self.assertGreater(res[3]['time'], UTCDateTime("2010-05-27T16:27:01"))
self.assertTrue(res[3]['time'] < UTCDateTime("2010-05-27T16:27:02"))
self.assertTrue(1.5 < res[3]['duration'] < 1.7)
self.assertEqual(res[3]['stations'], ['UH3', 'UH1'])
self.assertEqual(res[3]['coincidence_sum'], 2.0)
# 7. same as 3 but modify input trace ids and check output of trace_ids
# and other additional information with ``details=True``
st2 = st.copy()
st2[0].stats.network = "XX"
st2[1].stats.location = "99"
st2[1].stats.network = ""
st2[1].stats.location = "99"
st2[1].stats.channel = ""
st2[2].stats.channel = "EHN"
st2[3].stats.network = ""
st2[3].stats.channel = ""
st2[3].stats.station = ""
trace_ids = {'XX.UH1..SHZ': 0.4, '.UH2.99.': 0.35,
'BW.UH3..EHN': 0.4, '...': 0.25}
res = coincidence_trigger("recstalta", 3.5, 1, st2, 1.0,
trace_ids=trace_ids, details=True,
sta=0.5, lta=10)
self.assertEqual(len(res), 3)
self.assertGreater(res[0]['time'], UTCDateTime("2010-05-27T16:24:31"))
self.assertTrue(res[0]['time'] < UTCDateTime("2010-05-27T16:24:35"))
self.assertTrue(4.2 < res[0]['duration'] < 4.8)
self.assertEqual(res[0]['stations'], ['UH3', 'UH2', 'UH1', ''])
self.assertEqual(res[0]['trace_ids'][0], st2[2].id)
self.assertEqual(res[0]['trace_ids'][1], st2[1].id)
self.assertEqual(res[0]['trace_ids'][2], st2[0].id)
self.assertEqual(res[0]['trace_ids'][3], st2[3].id)
self.assertEqual(res[0]['coincidence_sum'], 1.4)
self.assertGreater(res[1]['time'], UTCDateTime("2010-05-27T16:26:59"))
self.assertTrue(res[1]['time'] < UTCDateTime("2010-05-27T16:27:03"))
self.assertTrue(3.2 < res[1]['duration'] < 3.7)
self.assertEqual(res[1]['stations'], ['UH2', 'UH3', 'UH1'])
self.assertEqual(res[1]['trace_ids'][0], st2[1].id)
self.assertEqual(res[1]['trace_ids'][1], st2[2].id)
self.assertEqual(res[1]['trace_ids'][2], st2[0].id)
self.assertEqual(res[1]['coincidence_sum'], 1.15)
self.assertGreater(res[2]['time'], UTCDateTime("2010-05-27T16:27:27"))
self.assertTrue(res[2]['time'] < UTCDateTime("2010-05-27T16:27:33"))
self.assertTrue(4.2 < res[2]['duration'] < 4.4)
self.assertEqual(res[2]['stations'], ['UH3', 'UH2', 'UH1', ''])
self.assertEqual(res[2]['trace_ids'][0], st2[2].id)
self.assertEqual(res[2]['trace_ids'][1], st2[1].id)
self.assertEqual(res[2]['trace_ids'][2], st2[0].id)
self.assertEqual(res[2]['trace_ids'][3], st2[3].id)
self.assertEqual(res[2]['coincidence_sum'], 1.4)
expected_keys = ['cft_peak_wmean', 'cft_std_wmean', 'cft_peaks',
'cft_stds']
expected_types = [float, float, list, list]
for item in res:
for key, _type in zip(expected_keys, expected_types):
self.assertIn(key, item)
self.assertTrue(isinstance(item[key], _type))
# check some of the detailed info
ev = res[-1]
self.assertAlmostEqual(ev['cft_peak_wmean'], 18.101139518271076,
places=5)
self.assertAlmostEqual(ev['cft_std_wmean'], 4.800051726246676,
places=5)
self.assertAlmostEqual(ev['cft_peaks'][0], 18.985548683223936,
places=5)
self.assertAlmostEqual(ev['cft_peaks'][1], 16.852175794415011,
places=5)
self.assertAlmostEqual(ev['cft_peaks'][2], 18.64005853900883,
places=5)
self.assertAlmostEqual(ev['cft_peaks'][3], 17.572363634564621,
places=5)
self.assertAlmostEqual(ev['cft_stds'][0], 4.8909448258821362,
places=5)
self.assertAlmostEqual(ev['cft_stds'][1], 4.4446373508521804,
places=5)
self.assertAlmostEqual(ev['cft_stds'][2], 5.3499401252675964,
places=5)
self.assertAlmostEqual(ev['cft_stds'][3], 4.2723814539487703,
places=5)
def test_coincidence_trigger_with_similarity_checking(self):
"""
Test network coincidence trigger with cross correlation similarity
checking of given event templates.
"""
st = Stream()
files = ["BW.UH1._.SHZ.D.2010.147.cut.slist.gz",
"BW.UH2._.SHZ.D.2010.147.cut.slist.gz",
"BW.UH3._.SHZ.D.2010.147.cut.slist.gz",
"BW.UH3._.SHN.D.2010.147.cut.slist.gz",
"BW.UH3._.SHE.D.2010.147.cut.slist.gz",
"BW.UH4._.EHZ.D.2010.147.cut.slist.gz"]
for filename in files:
filename = os.path.join(self.path, filename)
st += read(filename)
# some prefiltering used for UH network
st.filter('bandpass', freqmin=10, freqmax=20)
# set up template event streams
times = ["2010-05-27T16:24:33.095000", "2010-05-27T16:27:30.370000"]
templ = {}
for t in times:
t = UTCDateTime(t)
st_ = st.select(station="UH3").slice(t, t + 2.5).copy()
templ.setdefault("UH3", []).append(st_)
times = ["2010-05-27T16:27:30.574999"]
for t in times:
t = UTCDateTime(t)
st_ = st.select(station="UH1").slice(t, t + 2.5).copy()
templ.setdefault("UH1", []).append(st_)
# add another template with different SEED ID, it should be ignored
# (this can happen when using many templates over a long time period
# and instrument changes over time)
st_ = st_.copy()
for tr in st_:
tr.stats.channel = 'X' + tr.stats.channel[1:]
templ['UH1'].insert(0, st_)
trace_ids = {"BW.UH1..SHZ": 1,
"BW.UH2..SHZ": 1,
"BW.UH3..SHZ": 1,
"BW.UH4..EHZ": 1}
similarity_thresholds = {"UH1": 0.8, "UH3": 0.7}
with warnings.catch_warnings(record=True) as w:
# avoid getting influenced by the warning filters getting set up
# differently in obspy-runtests.
# (e.g. depending on options "-v" and "-q")
warnings.resetwarnings()
trig = coincidence_trigger(
"classicstalta", 5, 1, st.copy(), 4, sta=0.5, lta=10,
trace_ids=trace_ids, event_templates=templ,
similarity_threshold=similarity_thresholds)
# four warnings get raised
self.assertEqual(len(w), 4)
self.assertEqual(
str(w[0].message),
"At least one trace's ID was not found in the trace ID list and "
"was disregarded (BW.UH3..SHN)")
self.assertEqual(
str(w[1].message),
"At least one trace's ID was not found in the trace ID list and "
"was disregarded (BW.UH3..SHE)")
self.assertEqual(
str(w[2].message),
'Skipping trace BW.UH1..XHZ in template correlation (not present '
'in stream to check).')
self.assertEqual(
str(w[3].message),
"Skipping template(s) for station 'UH1': No common SEED IDs when "
"comparing template (BW.UH1..XHZ) and data streams (BW.UH1..SHZ, "
"BW.UH2..SHZ, BW.UH3..SHE, BW.UH3..SHN, BW.UH3..SHZ, "
"BW.UH4..EHZ).")
# check floats in resulting dictionary separately
self.assertAlmostEqual(trig[0].pop('duration'), 3.96, places=6)
self.assertAlmostEqual(trig[1].pop('duration'), 1.99, places=6)
self.assertAlmostEqual(trig[2].pop('duration'), 1.92, places=6)
self.assertAlmostEqual(trig[3].pop('duration'), 3.92, places=6)
self.assertAlmostEqual(trig[0]['similarity'].pop('UH1'),
0.94149447384, places=6)
self.assertAlmostEqual(trig[0]['similarity'].pop('UH3'), 1,
places=6)
self.assertAlmostEqual(trig[1]['similarity'].pop('UH1'),
0.65228204570, places=6)
self.assertAlmostEqual(trig[1]['similarity'].pop('UH3'),
0.72679293429, places=6)
self.assertAlmostEqual(trig[2]['similarity'].pop('UH1'),
0.89404458774, places=6)
self.assertAlmostEqual(trig[2]['similarity'].pop('UH3'),
0.74581409371, places=6)
self.assertAlmostEqual(trig[3]['similarity'].pop('UH1'), 1,
places=6)
self.assertAlmostEqual(trig[3]['similarity'].pop('UH3'), 1,
places=6)
remaining_results = \
[{'coincidence_sum': 4.0,
'similarity': {},
'stations': ['UH3', 'UH2', 'UH1', 'UH4'],
'time': UTCDateTime(2010, 5, 27, 16, 24, 33, 210000),
'trace_ids': ['BW.UH3..SHZ', 'BW.UH2..SHZ', 'BW.UH1..SHZ',
'BW.UH4..EHZ']},
{'coincidence_sum': 3.0,
'similarity': {},
'stations': ['UH3', 'UH1', 'UH2'],
'time': UTCDateTime(2010, 5, 27, 16, 25, 26, 710000),
'trace_ids': ['BW.UH3..SHZ', 'BW.UH1..SHZ', 'BW.UH2..SHZ']},
{'coincidence_sum': 3.0,
'similarity': {},
'stations': ['UH2', 'UH1', 'UH3'],
'time': UTCDateTime(2010, 5, 27, 16, 27, 2, 260000),
'trace_ids': ['BW.UH2..SHZ', 'BW.UH1..SHZ', 'BW.UH3..SHZ']},
{'coincidence_sum': 4.0,
'similarity': {},
'stations': ['UH3', 'UH2', 'UH1', 'UH4'],
'time': UTCDateTime(2010, 5, 27, 16, 27, 30, 510000),
'trace_ids': ['BW.UH3..SHZ', 'BW.UH2..SHZ', 'BW.UH1..SHZ',
'BW.UH4..EHZ']}]
self.assertEqual(trig, remaining_results)
def test_classic_sta_lta_c_python(self):
"""
Test case for ctypes version of recursive_sta_lta
"""
nsta, nlta = 5, 10
c1 = classic_sta_lta(self.data, nsta, nlta)
c2 = classic_sta_lta_py(self.data, nsta, nlta)
self.assertTrue(np.allclose(c1, c2, rtol=1e-10))
ref = np.array([0.38012302, 0.37704431, 0.47674533, 0.67992292])
self.assertTrue(np.allclose(ref, c2[99:103]))
def suite():
return unittest.makeSuite(TriggerTestCase, 'test')
if __name__ == '__main__':
unittest.main(defaultTest='suite')