def getStationMetrics(self, eventid, station, label):
"""Extract a StationSummary object from the ASDF file for a given input Stream.
Args:
eventid (str):
ID of event to search for in ASDF file.
station (str):
Station to return metrics from.
label (str):
Processing label to return metrics from.
Returns:
StationSummary: Object containing all stream metrics.
"""
if 'WaveFormMetrics' not in self.dataset.auxiliary_data:
raise KeyError('Waveform metrics not found in workspace.')
auxholder = self.dataset.auxiliary_data.WaveFormMetrics
stream_path = '%s_%s_%s' % (eventid, station.lower(), label)
if stream_path not in auxholder:
fmt = 'Waveform metrics for event %s and stream %s not found in workspace.'
raise KeyError(fmt % (eventid, tag))
bytelist = auxholder[stream_path].data[:].tolist()
xmlstr = ''.join([chr(b) for b in bytelist])
summary = StationSummary.fromMetricXML(xmlstr.encode('utf-8'))
return summary
def getStreamMetrics(self, eventid, station, label):
"""Extract a StationSummary object from the ASDF file for a given input Stream.
Args:
eventid (str):
ID of event to search for in ASDF file.
station (str):
Station to return metrics from.
label (str):
Processing label to return metrics from.
Returns:
StationSummary: Object containing all stream metrics.
"""
if 'WaveFormMetrics' not in self.dataset.auxiliary_data:
raise KeyError('Waveform metrics not found in workspace.')
auxholder = self.dataset.auxiliary_data.WaveFormMetrics
stream_path = '%s_%s_%s' % (eventid, station.lower(), label)
if stream_path not in auxholder:
fmt = 'Waveform metrics for event %s and stream %s not found in workspace.'
raise KeyError(fmt % (eventid, tag))
bytelist = auxholder[stream_path].data[:].tolist()
xmlstr = ''.join([chr(b) for b in bytelist])
summary = StationSummary.fromMetricXML(xmlstr.encode('utf-8'))
return summary
def test_stationsummary():
datafiles, _ = read_data_dir('geonet', 'us1000778i',
'20161113_110259_WTMC_20.V2A')
datafile = datafiles[0]
target_imcs = np.sort(
np.asarray([
'GREATER_OF_TWO_HORIZONTALS', 'HN1', 'HN2', 'HNZ', 'ROTD50.0',
'ROTD100.0'
]))
target_imts = np.sort(np.asarray(['SA(1.0)', 'PGA', 'PGV']))
stream = read_geonet(datafile)[0]
with warnings.catch_warnings():
warnings.simplefilter("ignore")
stream_summary = StationSummary.from_stream(stream, [
'greater_of_two_horizontals', 'channels', 'rotd50', 'rotd100',
'invalid'
], ['sa1.0', 'PGA', 'pgv', 'invalid'])
original_stream = stream_summary.stream
stream_summary.stream = []
final_stream = stream_summary.stream
assert original_stream == final_stream
original_code = stream_summary.station_code
stream_summary.station_code = ''
final_code = stream_summary.station_code
assert original_code == final_code
original_oscillators = stream_summary.oscillators
final_oscillators = stream_summary.oscillators
assert original_oscillators == final_oscillators
np.testing.assert_array_equal(np.sort(stream_summary.components),
target_imcs)
np.testing.assert_array_equal(np.sort(stream_summary.imts),
target_imts)
np.testing.assert_almost_equal(stream_summary.get_pgm('PGA', 'HN1'),
99.3173469387755,
decimal=1)
target_available = np.sort(
np.asarray([
'calculate_greater_of_two_horizontals',
'calculate_geometric_mean', 'calculate_channels',
'calculate_gmrotd', 'calculate_rotd',
'calculate_radial_transverse'
]))
imcs = stream_summary.available_imcs
np.testing.assert_array_equal(np.sort(imcs), target_available)
target_available = np.sort(
np.asarray([
'calculate_pga', 'calculate_pgv', 'calculate_sa',
'calculate_arias', 'calculate_fas'
]))
imts = stream_summary.available_imts
np.testing.assert_array_equal(np.sort(imts), target_available)
test_pgms = {
'PGV': {
'ROTD100.0': 114.24894584734818,
'ROTD50.0': 81.55436750525355,
'HNZ': 37.47740000000001,
'HN1': 100.81460000000004,
'HN2': 68.4354,
'GREATER_OF_TWO_HORIZONTALS': 100.81460000000004
},
'PGA': {
'ROTD100.0': 100.73875535385548,
'ROTD50.0': 91.40178541935455,
'HNZ': 183.7722361866693,
'HN1': 99.24999872535474,
'HN2': 81.23467239067368,
'GREATER_OF_TWO_HORIZONTALS': 99.24999872535474
},
'SA(1.0)': {
'ROTD100.0': 146.9023350124098,
'ROTD50.0': 106.03202302692158,
'HNZ': 27.74118995438756,
'HN1': 136.25041187387063,
'HN2': 84.69296738413021,
'GREATER_OF_TWO_HORIZONTALS': 136.25041187387063
}
}
datafiles, _ = read_data_dir('geonet', 'us1000778i',
'20161113_110313_THZ_20.V2A')
datafile = datafiles[0]
invalid_stream = read_geonet(datafile)[0]
station_code = 'WTMC'
pgm_summary = StationSummary.from_pgms(station_code, test_pgms)
adict = pgm_summary.pgms
bdict = stream_summary.pgms
cmp_dicts(adict, bdict)
# oscillators cannot be calculated without a stream
try:
pgm_summary.generate_oscillators(pgm_summary.imts, 0.05)
success = True
except Exception:
success = False
assert success is False
# Invalid stream inputs should be rejected
with warnings.catch_warnings():
warnings.simplefilter("ignore")
pgm_summary.stream = []
assert pgm_summary.stream is None
pgm_summary.stream = invalid_stream
assert pgm_summary.stream is None
pgm_summary.stream = stream
assert pgm_summary.stream == stream
# Test with fas
stream = read_geonet(datafile)[0]
stream_summary = StationSummary.from_stream(
stream, ['greater_of_two_horizontals', 'channels', 'geometric_mean'],
['sa1.0', 'PGA', 'pgv', 'fas2.0'])
target_imcs = np.sort(
np.asarray([
'GREATER_OF_TWO_HORIZONTALS', 'HN1', 'HN2', 'HNZ', 'GEOMETRIC_MEAN'
]))
target_imts = np.sort(np.asarray(['SA(1.0)', 'PGA', 'PGV', 'FAS(2.0)']))
np.testing.assert_array_equal(np.sort(stream_summary.components),
target_imcs)
np.testing.assert_array_equal(np.sort(stream_summary.imts), target_imts)
# Test config use
stream = read_geonet(datafile)[0]
stream_summary = StationSummary.from_stream(stream)
target_imcs = np.sort(
np.asarray(['GREATER_OF_TWO_HORIZONTALS', 'HN1', 'HN2', 'HNZ']))
target_imts = np.sort(
np.asarray([
'SA(1.0)', 'SA(2.0)', 'SA(3.0)', 'SA(0.3)', 'PGA', 'PGV',
'FAS(1.0)', 'FAS(2.0)', 'FAS(3.0)', 'FAS(0.3)'
]))
assert (stream_summary.smoothing == 'konno_ohmachi')
assert (stream_summary.bandwidth == 20.0)
assert (stream_summary.damping == 0.05)
# test XML output
stream = read_geonet(datafile)[0]
imclist = ['greater_of_two_horizontals', 'channels', 'rotd50', 'rotd100']
imtlist = ['sa1.0', 'PGA', 'pgv', 'fas2.0', 'arias']
stream_summary = StationSummary.from_stream(stream, imclist, imtlist)
xmlstr = stream_summary.getMetricXML()
print(xmlstr.decode('utf-8'))
stream2 = StationSummary.fromMetricXML(xmlstr)
cmp1 = np.sort(stream_summary.components)
cmp2 = np.sort(stream2.components)
np.testing.assert_array_equal(cmp1, cmp2)
imt1 = np.sort(stream_summary.imts)
imt2 = np.sort(stream2.imts)
np.testing.assert_array_equal(imt1, imt2)
def test_stationsummary():
datafiles, _ = read_data_dir(
'geonet', 'us1000778i', '20161113_110259_WTMC_20.V2A')
datafile = datafiles[0]
origin = Origin(latitude=42.6925, longitude=173.021944)
target_imcs = np.sort(np.asarray(['GREATER_OF_TWO_HORIZONTALS',
'HN1', 'HN2', 'HNZ', 'ROTD(50.0)',
'ROTD(100.0)']))
target_imts = np.sort(np.asarray(['SA(1.0)', 'PGA', 'PGV']))
stream = read_geonet(datafile)[0]
with warnings.catch_warnings():
warnings.simplefilter("ignore")
stream_summary = StationSummary.from_stream(
stream,
['greater_of_two_horizontals',
'channels',
'rotd50',
'rotd100',
'invalid'],
['sa1.0', 'PGA', 'pgv', 'invalid'], origin)
original_stream = stream_summary.stream
stream_summary.stream = []
final_stream = stream_summary.stream
assert original_stream == final_stream
original_code = stream_summary.station_code
np.testing.assert_array_equal(np.sort(stream_summary.components),
target_imcs)
np.testing.assert_array_equal(np.sort(stream_summary.imts),
target_imts)
np.testing.assert_almost_equal(stream_summary.get_pgm('PGA', 'HN1'),
99.3173469387755, decimal=1)
target_available = np.sort(np.asarray([
'greater_of_two_horizontals', 'geometric_mean', 'arithmetic_mean',
'channels', 'gmrotd', 'rotd', 'quadratic_mean',
'radial_transverse']))
imcs = stream_summary.available_imcs
np.testing.assert_array_equal(np.sort(imcs), target_available)
target_available = np.sort(np.asarray(['pga',
'pgv',
'sa',
'arias',
'fas']))
imts = stream_summary.available_imts
np.testing.assert_array_equal(np.sort(imts), target_available)
test_pgms = {
'PGV': {
'ROTD(100.0)': 114.24894584734818,
'ROTD(50.0)': 81.55436750525355,
'HNZ': 37.47740000000001,
'HN1': 100.81460000000004,
'HN2': 68.4354,
'GREATER_OF_TWO_HORIZONTALS': 100.81460000000004},
'PGA': {
'ROTD(100.0)': 100.73875535385548,
'ROTD(50.0)': 91.40178541935455,
'HNZ': 183.7722361866693,
'HN1': 99.24999872535474,
'HN2': 81.23467239067368,
'GREATER_OF_TWO_HORIZONTALS': 99.24999872535474},
'SA(1.0)': {
'ROTD(100.0)': 146.9023350124098,
'ROTD(50.0)': 106.03202302692158,
'HNZ': 27.74118995438756,
'HN1': 136.25041187387063,
'HN2': 84.69296738413021,
'GREATER_OF_TWO_HORIZONTALS': 136.25041187387063}
}
pgms = stream_summary.pgms
for imt_str in test_pgms:
for imc_str in test_pgms[imt_str]:
imt = pgms.loc[pgms['IMT'] == imt_str]
imc = imt.loc[imt['IMC'] == imc_str]
results = imc.Result.tolist()
assert len(results) == 1
np.testing.assert_almost_equal(results[0], test_pgms[imt_str][imc_str],
decimal=10)
# Test with fas
stream = read_geonet(datafile)[0]
stream_summary = StationSummary.from_stream(
stream,
['greater_of_two_horizontals',
'channels',
'geometric_mean'],
['sa1.0', 'PGA', 'pgv', 'fas2.0'])
target_imcs = np.sort(np.asarray(['GREATER_OF_TWO_HORIZONTALS',
'HN1', 'HN2', 'HNZ',
'GEOMETRIC_MEAN']))
target_imts = np.sort(np.asarray(['SA(1.0)',
'PGA', 'PGV', 'FAS(2.0)']))
np.testing.assert_array_equal(np.sort(stream_summary.components),
target_imcs)
np.testing.assert_array_equal(np.sort(stream_summary.imts),
target_imts)
# Test config use
stream = read_geonet(datafile)[0]
stream_summary = StationSummary.from_config(stream)
target_imcs = np.sort(np.asarray(['GREATER_OF_TWO_HORIZONTALS',
'HN1', 'HN2', 'HNZ']))
target_imts = np.sort(np.asarray(['SA(1.0)', 'SA(2.0)', 'SA(3.0)',
'SA(0.3)', 'PGA', 'PGV', 'FAS(1.0)', 'FAS(2.0)',
'FAS(3.0)', 'FAS(0.3)']))
assert(stream_summary.smoothing == 'konno_ohmachi')
assert(stream_summary.bandwidth == 20.0)
assert(stream_summary.damping == 0.05)
# test XML output
stream = read_geonet(datafile)[0]
imclist = ['greater_of_two_horizontals',
'channels',
'rotd50.0',
'rotd100.0']
imtlist = ['sa1.0', 'PGA', 'pgv', 'fas2.0', 'arias']
stream_summary = StationSummary.from_stream(stream, imclist, imtlist)
xmlstr = stream_summary.getMetricXML()
print(xmlstr.decode('utf-8'))
stream2 = StationSummary.fromMetricXML(xmlstr)
cmp1 = np.sort(['GREATER_OF_TWO_HORIZONTALS', 'HN1', 'HN2', 'HNZ',
'ROTD100.0', 'ROTD50.0'])
cmp2 = np.sort(stream2.components)
np.testing.assert_array_equal(cmp1, cmp2)
imt1 = np.sort(stream_summary.imts)
imt2 = np.sort(stream2.imts)
np.testing.assert_array_equal(imt1, imt2)
