def test_metrics():
eventid = 'usb000syza'
datafiles, event = read_data_dir('knet', eventid, '*')
datadir = os.path.split(datafiles[0])[0]
raw_streams = StreamCollection.from_directory(datadir)
config = get_config()
# turn off sta/lta check and snr checks
newconfig = drop_processing(config, ['check_sta_lta', 'compute_snr'])
processed_streams = process_streams(raw_streams, event, config=newconfig)
tdir = tempfile.mkdtemp()
try:
tfile = os.path.join(tdir, 'test.hdf')
workspace = StreamWorkspace(tfile)
workspace.addEvent(event)
workspace.addStreams(event, processed_streams, label='processed')
stream1 = processed_streams[0]
stream2 = processed_streams[1]
summary1 = StationSummary.from_config(stream1)
summary2 = StationSummary.from_config(stream2)
workspace.setStreamMetrics(event.id, 'processed', summary1)
workspace.setStreamMetrics(event.id, 'processed', summary2)
workspace.calcStationMetrics(event.id, labels=['processed'])
summary1_a = workspace.getStreamMetrics(event.id,
stream1[0].stats.station,
'processed')
s1_df_in = summary1.pgms.sort_values(['IMT', 'IMC'])
s1_df_out = summary1_a.pgms.sort_values(['IMT', 'IMC'])
array1 = s1_df_in['Result'].as_matrix()
array2 = s1_df_out['Result'].as_matrix()
np.testing.assert_almost_equal(array1, array2, decimal=4)
df = workspace.getMetricsTable(event.id)
cmp_series = {
'GREATER_OF_TWO_HORIZONTALS': 0.6787,
'H1': 0.3869,
'H2': 0.6787,
'Z': 0.7663
}
pga_dict = df.iloc[0]['PGA'].to_dict()
for key, value in pga_dict.items():
value2 = cmp_series[key]
np.testing.assert_almost_equal(value, value2, decimal=4)
workspace.close()
except Exception as e:
raise(e)
finally:
shutil.rmtree(tdir)
def test_metrics():
eventid = 'usb000syza'
datafiles, event = read_data_dir('knet', eventid, '*')
datadir = os.path.split(datafiles[0])[0]
raw_streams = StreamCollection.from_directory(datadir)
config = get_config()
# turn off sta/lta check and snr checks
# newconfig = drop_processing(config, ['check_sta_lta', 'compute_snr'])
# processed_streams = process_streams(raw_streams, event, config=newconfig)
newconfig = config.copy()
newconfig['processing'].append(
{'NNet_QA': {
'acceptance_threshold': 0.5,
'model_name': 'CantWell'
}})
processed_streams = process_streams(raw_streams, event, config=newconfig)
tdir = tempfile.mkdtemp()
try:
tfile = os.path.join(tdir, 'test.hdf')
workspace = StreamWorkspace(tfile)
workspace.addEvent(event)
workspace.addStreams(event, raw_streams, label='raw')
workspace.addStreams(event, processed_streams, label='processed')
stream1 = raw_streams[0]
summary1 = StationSummary.from_config(stream1)
s1_df_in = summary1.pgms.sort_values(['IMT', 'IMC'])
array1 = s1_df_in['Result'].as_matrix()
workspace.calcStreamMetrics(eventid, labels=['raw'])
workspace.calcStationMetrics(event.id, labels=['raw'])
pstreams2 = workspace.getStreams(event.id, labels=['processed'])
assert pstreams2[0].getStreamParamKeys() == ['nnet_qa']
summary1_a = workspace.getStreamMetrics(event.id,
stream1[0].stats.network,
stream1[0].stats.station,
'raw')
s1_df_out = summary1_a.pgms.sort_values(['IMT', 'IMC'])
array2 = s1_df_out['Result'].as_matrix()
np.testing.assert_almost_equal(array1, array2, decimal=4)
workspace.close()
except Exception as e:
raise (e)
finally:
shutil.rmtree(tdir)