def test_PPSD(self):
"""
Test PPSD routine with some real data.
"""
# paths of the expected result data
file_histogram = os.path.join(
self.path,
'BW.KW1._.EHZ.D.2011.090_downsampled__ppsd_hist_stack.npy')
file_binning = os.path.join(
self.path, 'BW.KW1._.EHZ.D.2011.090_downsampled__ppsd_mixed.npz')
file_mode_mean = os.path.join(
self.path,
'BW.KW1._.EHZ.D.2011.090_downsampled__ppsd_mode_mean.npz')
tr, paz = _get_sample_data()
st = Stream([tr])
ppsd = _get_ppsd()
# read results and compare
result_hist = np.load(file_histogram)
self.assertEqual(len(ppsd.times), 4)
self.assertEqual(ppsd.nfft, 65536)
self.assertEqual(ppsd.nlap, 49152)
np.testing.assert_array_equal(ppsd.hist_stack, result_hist)
# add the same data a second time (which should do nothing at all) and
# test again - but it will raise UserWarnings, which we omit for now
with warnings.catch_warnings(record=True):
warnings.simplefilter('ignore', UserWarning)
ppsd.add(st)
np.testing.assert_array_equal(ppsd.hist_stack, result_hist)
# test the binning arrays
binning = np.load(file_binning)
np.testing.assert_array_equal(ppsd.spec_bins, binning['spec_bins'])
np.testing.assert_array_equal(ppsd.period_bins, binning['period_bins'])
# test the mode/mean getter functions
per_mode, mode = ppsd.get_mode()
per_mean, mean = ppsd.get_mean()
result_mode_mean = np.load(file_mode_mean)
np.testing.assert_array_equal(per_mode, result_mode_mean['per_mode'])
np.testing.assert_array_equal(mode, result_mode_mean['mode'])
np.testing.assert_array_equal(per_mean, result_mode_mean['per_mean'])
np.testing.assert_array_equal(mean, result_mode_mean['mean'])
# test saving and loading of the PPSD (using a temporary file)
with NamedTemporaryFile() as tf:
filename = tf.name
# test saving and loading an uncompressed file
ppsd.save(filename, compress=False)
ppsd_loaded = PPSD.load(filename)
self.assertEqual(len(ppsd_loaded.times), 4)
self.assertEqual(ppsd_loaded.nfft, 65536)
self.assertEqual(ppsd_loaded.nlap, 49152)
np.testing.assert_array_equal(ppsd_loaded.hist_stack, result_hist)
np.testing.assert_array_equal(ppsd_loaded.spec_bins,
binning['spec_bins'])
np.testing.assert_array_equal(ppsd_loaded.period_bins,
binning['period_bins'])
# test saving and loading a compressed file
ppsd.save(filename, compress=True)
ppsd_loaded = PPSD.load(filename)
self.assertEqual(len(ppsd_loaded.times), 4)
self.assertEqual(ppsd_loaded.nfft, 65536)
self.assertEqual(ppsd_loaded.nlap, 49152)
np.testing.assert_array_equal(ppsd_loaded.hist_stack, result_hist)
np.testing.assert_array_equal(ppsd_loaded.spec_bins,
binning['spec_bins'])
np.testing.assert_array_equal(ppsd_loaded.period_bins,
binning['period_bins'])
def test_PPSD(self):
"""
Test PPSD routine with some real data. Data was downsampled to 100Hz
so the ppsd is a bit distorted which does not matter for the purpose
of testing.
"""
# load test file
file_data = os.path.join(
self.path, 'BW.KW1._.EHZ.D.2011.090_downsampled.asc.gz')
file_histogram = os.path.join(
self.path,
'BW.KW1._.EHZ.D.2011.090_downsampled__ppsd_hist_stack.npy')
file_binning = os.path.join(
self.path, 'BW.KW1._.EHZ.D.2011.090_downsampled__ppsd_mixed.npz')
# parameters for the test
data = np.loadtxt(file_data)
stats = {'_format': 'MSEED',
'calib': 1.0,
'channel': 'EHZ',
'delta': 0.01,
'endtime': UTCDateTime(2011, 3, 31, 2, 36, 0, 180000),
'location': '',
'mseed': {'dataquality': 'D', 'record_length': 512,
'encoding': 'STEIM2', 'byteorder': '>'},
'network': 'BW',
'npts': 936001,
'sampling_rate': 100.0,
'starttime': UTCDateTime(2011, 3, 31, 0, 0, 0, 180000),
'station': 'KW1'}
tr = Trace(data, stats)
st = Stream([tr])
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]}
ppsd = PPSD(tr.stats, paz)
ppsd.add(st)
# read results and compare
result_hist = np.load(file_histogram)
self.assertEqual(len(ppsd.times), 4)
self.assertEqual(ppsd.nfft, 65536)
self.assertEqual(ppsd.nlap, 49152)
np.testing.assert_array_equal(ppsd.hist_stack, result_hist)
# add the same data a second time (which should do nothing at all) and
# test again - but it will raise UserWarnings, which we omit for now
with warnings.catch_warnings(record=True):
warnings.simplefilter('ignore', UserWarning)
ppsd.add(st)
np.testing.assert_array_equal(ppsd.hist_stack, result_hist)
# test the binning arrays
binning = np.load(file_binning)
np.testing.assert_array_equal(ppsd.spec_bins, binning['spec_bins'])
np.testing.assert_array_equal(ppsd.period_bins, binning['period_bins'])
# test saving and loading of the PPSD (using a temporary file)
with NamedTemporaryFile() as tf:
filename = tf.name
# test saving and loading an uncompressed file
ppsd.save(filename, compress=False)
ppsd_loaded = PPSD.load(filename)
self.assertEqual(len(ppsd_loaded.times), 4)
self.assertEqual(ppsd_loaded.nfft, 65536)
self.assertEqual(ppsd_loaded.nlap, 49152)
np.testing.assert_array_equal(ppsd_loaded.hist_stack, result_hist)
np.testing.assert_array_equal(ppsd_loaded.spec_bins,
binning['spec_bins'])
np.testing.assert_array_equal(ppsd_loaded.period_bins,
binning['period_bins'])
# test saving and loading a compressed file
ppsd.save(filename, compress=True)
ppsd_loaded = PPSD.load(filename)
self.assertEqual(len(ppsd_loaded.times), 4)
self.assertEqual(ppsd_loaded.nfft, 65536)
self.assertEqual(ppsd_loaded.nlap, 49152)
np.testing.assert_array_equal(ppsd_loaded.hist_stack, result_hist)
np.testing.assert_array_equal(ppsd_loaded.spec_bins,
binning['spec_bins'])
np.testing.assert_array_equal(ppsd_loaded.period_bins,
binning['period_bins'])
def test_PPSD(self):
"""
Test PPSD routine with some real data. Data was downsampled to 100Hz
so the ppsd is a bit distorted which does not matter for the purpose
of testing.
"""
# load test file
file_data = os.path.join(self.path,
'BW.KW1._.EHZ.D.2011.090_downsampled.asc.gz')
file_histogram = os.path.join(
self.path,
'BW.KW1._.EHZ.D.2011.090_downsampled__ppsd_hist_stack.npy')
file_binning = os.path.join(
self.path, 'BW.KW1._.EHZ.D.2011.090_downsampled__ppsd_mixed.npz')
# parameters for the test
# no with due to py 2.6
f = gzip.open(file_data)
data = np.loadtxt(f)
f.close()
stats = {
'_format': 'MSEED',
'calib': 1.0,
'channel': 'EHZ',
'delta': 0.01,
'endtime': UTCDateTime(2011, 3, 31, 2, 36, 0, 180000),
'location': '',
'mseed': {
'dataquality': 'D',
'record_length': 512,
'encoding': 'STEIM2',
'byteorder': '>'
},
'network': 'BW',
'npts': 936001,
'sampling_rate': 100.0,
'starttime': UTCDateTime(2011, 3, 31, 0, 0, 0, 180000),
'station': 'KW1'
}
tr = Trace(data, stats)
st = Stream([tr])
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]
}
ppsd = PPSD(tr.stats, paz, db_bins=(-200, -50, 0.5))
ppsd.add(st)
# read results and compare
result_hist = np.load(file_histogram)
self.assertEqual(len(ppsd.times), 4)
self.assertEqual(ppsd.nfft, 65536)
self.assertEqual(ppsd.nlap, 49152)
np.testing.assert_array_equal(ppsd.hist_stack, result_hist)
# add the same data a second time (which should do nothing at all) and
# test again - but it will raise UserWarnings, which we omit for now
with warnings.catch_warnings(record=True):
warnings.simplefilter('ignore', UserWarning)
ppsd.add(st)
np.testing.assert_array_equal(ppsd.hist_stack, result_hist)
# test the binning arrays
binning = np.load(file_binning)
np.testing.assert_array_equal(ppsd.spec_bins, binning['spec_bins'])
np.testing.assert_array_equal(ppsd.period_bins, binning['period_bins'])
# test saving and loading of the PPSD (using a temporary file)
with NamedTemporaryFile() as tf:
filename = tf.name
# test saving and loading an uncompressed file
ppsd.save(filename, compress=False)
ppsd_loaded = PPSD.load(filename)
self.assertEqual(len(ppsd_loaded.times), 4)
self.assertEqual(ppsd_loaded.nfft, 65536)
self.assertEqual(ppsd_loaded.nlap, 49152)
np.testing.assert_array_equal(ppsd_loaded.hist_stack, result_hist)
np.testing.assert_array_equal(ppsd_loaded.spec_bins,
binning['spec_bins'])
np.testing.assert_array_equal(ppsd_loaded.period_bins,
binning['period_bins'])
# test saving and loading a compressed file
ppsd.save(filename, compress=True)
ppsd_loaded = PPSD.load(filename)
self.assertEqual(len(ppsd_loaded.times), 4)
self.assertEqual(ppsd_loaded.nfft, 65536)
self.assertEqual(ppsd_loaded.nlap, 49152)
np.testing.assert_array_equal(ppsd_loaded.hist_stack, result_hist)
np.testing.assert_array_equal(ppsd_loaded.spec_bins,
binning['spec_bins'])
np.testing.assert_array_equal(ppsd_loaded.period_bins,
binning['period_bins'])
def test_PPSD(self):
"""
Test PPSD routine with some real data.
"""
# paths of the expected result data
file_histogram = os.path.join(
self.path,
'BW.KW1._.EHZ.D.2011.090_downsampled__ppsd_hist_stack.npy')
file_binning = os.path.join(
self.path, 'BW.KW1._.EHZ.D.2011.090_downsampled__ppsd_mixed.npz')
file_mode_mean = os.path.join(
self.path,
'BW.KW1._.EHZ.D.2011.090_downsampled__ppsd_mode_mean.npz')
tr, paz = _get_sample_data()
st = Stream([tr])
ppsd = _get_ppsd()
# read results and compare
result_hist = np.load(file_histogram)
self.assertEqual(len(ppsd.times), 4)
self.assertEqual(ppsd.nfft, 65536)
self.assertEqual(ppsd.nlap, 49152)
np.testing.assert_array_equal(ppsd.hist_stack, result_hist)
# add the same data a second time (which should do nothing at all) and
# test again - but it will raise UserWarnings, which we omit for now
with warnings.catch_warnings(record=True):
warnings.simplefilter('ignore', UserWarning)
ppsd.add(st)
np.testing.assert_array_equal(ppsd.hist_stack, result_hist)
# test the binning arrays
binning = np.load(file_binning)
np.testing.assert_array_equal(ppsd.spec_bins, binning['spec_bins'])
np.testing.assert_array_equal(ppsd.period_bins, binning['period_bins'])
# test the mode/mean getter functions
per_mode, mode = ppsd.get_mode()
per_mean, mean = ppsd.get_mean()
result_mode_mean = np.load(file_mode_mean)
np.testing.assert_array_equal(per_mode, result_mode_mean['per_mode'])
np.testing.assert_array_equal(mode, result_mode_mean['mode'])
np.testing.assert_array_equal(per_mean, result_mode_mean['per_mean'])
np.testing.assert_array_equal(mean, result_mode_mean['mean'])
# test saving and loading of the PPSD (using a temporary file)
with NamedTemporaryFile() as tf:
filename = tf.name
# test saving and loading an uncompressed file
ppsd.save(filename, compress=False)
ppsd_loaded = PPSD.load(filename)
self.assertEqual(len(ppsd_loaded.times), 4)
self.assertEqual(ppsd_loaded.nfft, 65536)
self.assertEqual(ppsd_loaded.nlap, 49152)
np.testing.assert_array_equal(ppsd_loaded.hist_stack, result_hist)
np.testing.assert_array_equal(ppsd_loaded.spec_bins,
binning['spec_bins'])
np.testing.assert_array_equal(ppsd_loaded.period_bins,
binning['period_bins'])
# test saving and loading a compressed file
ppsd.save(filename, compress=True)
ppsd_loaded = PPSD.load(filename)
self.assertEqual(len(ppsd_loaded.times), 4)
self.assertEqual(ppsd_loaded.nfft, 65536)
self.assertEqual(ppsd_loaded.nlap, 49152)
np.testing.assert_array_equal(ppsd_loaded.hist_stack, result_hist)
np.testing.assert_array_equal(ppsd_loaded.spec_bins,
binning['spec_bins'])
np.testing.assert_array_equal(ppsd_loaded.period_bins,
binning['period_bins'])
