def test_evalrespBug395(self):
"""
Was a bug due to inconstistent numerical range
"""
resp = os.path.join(self.path, 'RESP.CH._.HHZ.gz')
fh = NamedTemporaryFile()
tmpfile = fh.name
fh.write(gzip.open(resp).read())
fh.close()
samprate = 120.0
nfft = 56328
args = [1/samprate, nfft, tmpfile,
UTCDateTime(2012, 9, 4, 5, 12, 15, 863300)]
kwargs = {'units': 'VEL', 'freq': True}
h, f = evalresp(*args, **kwargs)
self.assertEquals(len(f), nfft // 2 + 1)
os.unlink(tmpfile)
def test_read_events(self):
"""
Tests reading a QuakeML document via read_events.
"""
with NamedTemporaryFile() as tf:
tmpfile = tf.name
catalog = read_events(self.neries_filename)
self.assertTrue(len(catalog), 3)
catalog.write(tmpfile, format='QUAKEML')
# Read file again. Avoid the (legit) warning about the already used
# resource identifiers.
with warnings.catch_warnings(record=True):
warnings.simplefilter("ignore")
catalog2 = read_events(tmpfile)
self.assertTrue(len(catalog2), 3)
def test_raise_on_empty_file(self):
"""
Test case ensures that empty files do raise warnings.
"""
with NamedTemporaryFile() as tf:
tmpfile = tf.name
# create empty file
open(tmpfile, 'wb').close()
formats_ep = _get_default_eps('obspy.plugin.waveform',
'readFormat')
# using format keyword
for ep in formats_ep.values():
is_format = load_entry_point(
ep.dist.key, 'obspy.plugin.waveform.' + ep.name,
'isFormat')
self.assertFalse(False, is_format(tmpfile))
def test_plotDefaultSection(self):
"""
Tests plotting 10 in a section
"""
start = UTCDateTime(0)
st = Stream()
for _i in range(10):
st += self._createStream(start, start + 3600, 100)
st[-1].stats.distance = _i * 10e3
# create and compare image
with NamedTemporaryFile(suffix='.png') as tf:
st.plot(outfile=tf.name, type='section')
# compare images
expected_image = os.path.join(self.path,
'waveform_default_section.png')
compare_images(tf.name, expected_image, 0.001)
def test_write_quakeml(self):
"""
Tests writing a QuakeML document.
"""
filename = os.path.join(self.path, 'qml-example-1.2-RC3.xml')
with NamedTemporaryFile() as tf:
tmpfile = tf.name
catalog = _read_quakeml(filename)
self.assertTrue(len(catalog), 1)
_write_quakeml(catalog, tmpfile, validate=IS_RECENT_LXML)
# Read file again. Avoid the (legit) warning about the already used
# resource identifiers.
with warnings.catch_warnings(record=True):
warnings.simplefilter("ignore")
catalog2 = _read_quakeml(tmpfile)
self.assertTrue(len(catalog2), 1)
def test_file_with_no_timing_quality(self):
"""
Tests timing quality extraction in files with no timing quality.
"""
with NamedTemporaryFile() as tf1:
obspy.Trace(data=np.arange(10, dtype=np.int32),
header={"starttime": obspy.UTCDateTime(0)}).write(
tf1.name, format="mseed")
mseed_metadata = MSEEDMetadata([tf1.name], add_flags=True)
ref = mseed_metadata.meta['miniseed_header_percentages']
self.assertEqual(ref['timing_quality_max'],
None)
self.assertEqual(ref['timing_quality_min'],
None)
self.assertEqual(ref['timing_quality_mean'],
None)
def wrapped_func(filename, *args, **kwargs):
if not isinstance(filename, basestring):
return func(filename, *args, **kwargs)
elif not os.path.exists(filename):
msg = "File not found '%s'" % (filename)
raise IOError(msg)
# check if we got a compressed file
unpacked_data = None
if filename.endswith('.bz2'):
# bzip2
try:
import bz2
unpacked_data = bz2.decompress(open(filename, 'rb').read())
except:
pass
elif filename.endswith('.gz'):
# gzip
try:
import gzip
unpacked_data = gzip.open(filename, 'rb').read()
except:
pass
if unpacked_data:
# we unpacked something without errors - create temporary file
tempfile = NamedTemporaryFile()
tempfile._fileobj.write(unpacked_data)
tempfile.close()
# call wrapped function
try:
result = func(tempfile.name, *args, **kwargs)
except:
# clean up unpacking procedure
if unpacked_data:
tempfile.close()
os.remove(tempfile.name)
raise
# clean up unpacking procedure
if unpacked_data:
tempfile.close()
os.remove(tempfile.name)
else:
# call wrapped function with original filename
result = func(filename, *args, **kwargs)
return result
def test_plotSimpleGapFewSamples(self):
"""
Plots three hours with a gap.
There are 45 minutes of data at the beginning and 45 minutes of data at
the end.
"""
start = UTCDateTime(0)
st = self._createStream(start, start + 3600 * 3 / 4, 5.0)
st += self._createStream(start + 2.25 * 3600, start + 3 * 3600, 5.0)
# create and compare image
with NamedTemporaryFile(suffix='.png') as tf:
st.plot(outfile=tf.name)
# compare images
expected_image = os.path.join(
self.path, 'waveform_simple_gap_few_samples.png')
compare_images(tf.name, expected_image, 0.001)
def test_plotOneHourManySamples(self):
"""
Plots one hour, starting Jan 1970.
Uses a frequency of 1000 Hz to get a sample count of over 3 Million and
get in the range, that plotting will choose to use a minimum maximum
approach to plot the data.
"""
start = UTCDateTime(0)
st = self._createStream(start, start + 3600, 1000.0)
# create and compare image
with NamedTemporaryFile(suffix='.png') as tf:
st.plot(outfile=tf.name)
# compare images
expected_image = os.path.join(
self.path, 'waveform_one_hour_many_samples.png')
compare_images(tf.name, expected_image, 0.001)
def test_evalrespBug395(self):
"""
Was a bug due to inconstistent numerical range
"""
resp = os.path.join(self.path, 'RESP.CH._.HHZ.gz')
with NamedTemporaryFile() as fh:
tmpfile = fh.name
fh.write(gzip.open(resp).read())
samprate = 120.0
nfft = 56328
args = [
1.0 / samprate, nfft, tmpfile,
UTCDateTime(2012, 9, 4, 5, 12, 15, 863300)
]
kwargs = {'units': 'VEL', 'freq': True}
_h, f = evalresp(*args, **kwargs)
self.assertEquals(len(f), nfft // 2 + 1)
def test_can_add_npz_without_pickle(self):
"""
Ensure PPSD can be added without using the pickle protocol, or
that a helpful error message is raised if allow_pickle is required.
See #2409.
"""
ppsd = _internal_get_ppsd()
# save PPSD in such a way to mock old versions.
with NamedTemporaryFile(suffix='.npz') as ntemp:
temp_path = ntemp.name
self._save_npz_require_pickle(temp_path, ppsd)
# We should be able to load the files when allowing pickle.
ppsd.add_npz(temp_path, allow_pickle=True)
# If not allow_pickle, a helpful error msg should be raised.
with pytest.raises(ValueError, match='Loading PPSD results'):
ppsd.add_npz(temp_path)
def test_PPSD_save_and_load_npz(self):
"""
Test PPSD.load_npz() and PPSD.save_npz()
"""
_, paz = _get_sample_data()
ppsd = _get_ppsd()
# save results to npz file
with NamedTemporaryFile(suffix=".npz") as tf:
filename = tf.name
# test saving and loading an uncompressed file
ppsd.save_npz(filename)
ppsd_loaded = PPSD.load_npz(filename, metadata=paz)
for key in NPZ_STORE_KEYS:
np.testing.assert_equal(getattr(ppsd, key),
getattr(ppsd_loaded, key))
def test_schema_validation(self):
with NamedTemporaryFile() as tf:
obspy.Trace(data=np.arange(10, dtype=np.int32),
header={"starttime": obspy.UTCDateTime(0)}).write(
tf.name, format="mseed")
md = MSEEDMetadata(files=[tf.name])
# One can either directly validate the metrics.
md.validate_qc_metrics(md.meta)
# Or do it during the serialization.
md.get_json_meta(validate=True)
# Also try with extracting the flags.
md = MSEEDMetadata(files=[tf.name], add_flags=True)
md.validate_qc_metrics(md.meta)
md.get_json_meta(validate=True)
def cmp_file(self, quakeml_file, sc3ml_file, path=None,
validate=True, event_removal=False):
"""
Check if the generated sc3ml file is the same than the one in the data
folder.
"""
if path is None:
path = self.quakeml_path
filename = os.path.join(path, quakeml_file)
catalog = _read_quakeml(filename)
with NamedTemporaryFile() as tf:
tmpfile = tf.name
catalog.write(tmpfile, format='SC3ML', validate=validate,
verbose=True, event_removal=event_removal)
filepath_cmp = os.path.join(self.path, sc3ml_file)
self.assertTrue(filecmp.cmp(filepath_cmp, tmpfile))
def test_gap_fire_testing(self):
"""
Fire tests at a rapid rate to test the gap function
Rapid gap testing. Create the following stream:
0 -- 1 -- x -- x -- 4 -- x -- x -- 7 -- 8 -- x -- 10 -- 11 --
And shoot as many strange windows, check if gaps are calculated
correctly. Add your own!
"""
tr_1 = obspy.Trace(data=np.arange(2, dtype=np.int32),
header={"starttime": obspy.UTCDateTime(5)})
tr_2 = obspy.Trace(data=np.arange(1, dtype=np.int32),
header={"starttime": obspy.UTCDateTime(9)})
tr_3 = obspy.Trace(data=np.arange(2, dtype=np.int32),
header={"starttime": obspy.UTCDateTime(12)})
tr_4 = obspy.Trace(data=np.arange(2, dtype=np.int32),
header={"starttime": obspy.UTCDateTime(15)})
st = obspy.Stream(traces=[tr_1, tr_2, tr_3, tr_4])
with NamedTemporaryFile() as tf:
st.write(tf.name, format="mseed")
def _rapid_gap_testing(start, end):
md = MSEEDMetadata(files=[tf.name],
starttime=obspy.UTCDateTime(start),
endtime=obspy.UTCDateTime(end))
return md.meta['sum_gaps']
self.assertTrue(_rapid_gap_testing(5, 17) == 5)
self.assertTrue(_rapid_gap_testing(5, 10) == 2)
self.assertTrue(_rapid_gap_testing(8.30, 9.5) == 0.70)
self.assertTrue(_rapid_gap_testing(9, 12) == 2)
self.assertTrue(_rapid_gap_testing(12, 17) == 1)
self.assertTrue(_rapid_gap_testing(10, 13) == 2)
self.assertTrue(_rapid_gap_testing(10.25, 13) == 1.75)
self.assertTrue(_rapid_gap_testing(11.75, 17) == 1.25)
self.assertTrue(_rapid_gap_testing(6, 10.5) == 2.5)
self.assertTrue(_rapid_gap_testing(11.99, 12.01) == 0.01)
self.assertTrue(_rapid_gap_testing(10.1, 12.01) == 1.9)
self.assertTrue(_rapid_gap_testing(7.5, 14.25) == 3.75)
self.assertTrue(_rapid_gap_testing(5, 17.5) == 5.5)
self.assertTrue(_rapid_gap_testing(5, 17.6) == 5.6)
self.assertTrue(_rapid_gap_testing(5, 18) == 6)
self.assertTrue(_rapid_gap_testing(0, 5.01) == 5)
self.assertTrue(_rapid_gap_testing(0, 20) == 13)
def wrapped_func(filename, *args, **kwargs):
if not isinstance(filename, basestring):
return func(filename, *args, **kwargs)
elif not os.path.exists(filename):
msg = "File not found '%s'" % (filename)
raise IOError(msg)
# check if we got a compressed file
unpacked_data = None
if filename.endswith(".bz2"):
# bzip2
try:
import bz2
unpacked_data = bz2.decompress(open(filename, "rb").read())
except:
pass
elif filename.endswith(".gz"):
# gzip
try:
import gzip
unpacked_data = gzip.open(filename, "rb").read()
except:
pass
if unpacked_data:
# we unpacked something without errors - create temporary file
tempfile = NamedTemporaryFile()
tempfile._fileobj.write(unpacked_data)
tempfile.close()
# call wrapped function
try:
result = func(tempfile.name, *args, **kwargs)
except:
# clean up unpacking procedure
if unpacked_data:
tempfile.close()
os.remove(tempfile.name)
raise
# clean up unpacking procedure
if unpacked_data:
tempfile.close()
os.remove(tempfile.name)
else:
# call wrapped function with original filename
result = func(filename, *args, **kwargs)
return result
def test_write_preferred_origin(self):
event = full_test_event()
preferred_origin = Origin(time=UTCDateTime("2012-03-26") + 2.2,
latitude=47.0,
longitude=35.0,
depth=18000)
event.origins.append(preferred_origin)
event.preferred_origin_id = preferred_origin.resource_id
with NamedTemporaryFile(suffix=".out") as tf:
event.write(tf.name, format="NORDIC")
event_back = read_events(tf.name)
self.assertEqual(preferred_origin.latitude,
event_back[0].origins[0].latitude)
self.assertEqual(preferred_origin.longitude,
event_back[0].origins[0].longitude)
self.assertEqual(preferred_origin.depth,
event_back[0].origins[0].depth)
self.assertEqual(preferred_origin.time,
event_back[0].origins[0].time)
def cmp_write_xslt_file(self, quakeml_file, sc3ml_file, validate=True,
path=None):
"""
Check if the SC3ML file generated with the XSLT file is the
same than the one in the data folder.
"""
if path is None:
path = self.path
transform = etree.XSLT(etree.parse(self.write_xslt_filename))
filename = os.path.join(path, quakeml_file)
sc3ml_doc = transform(etree.parse(filename))
with NamedTemporaryFile() as tf:
tf.write(sc3ml_doc)
if validate:
self.assertTrue(validate_sc3ml(tf.name))
filepath_cmp = os.path.join(self.path, sc3ml_file)
self.assertTrue(filecmp.cmp(filepath_cmp, tf.name))
def test_writeQuakeML(self):
"""
Tests writing a QuakeML document.
skipIfPython25 due to the use of the warnings context manager.
"""
filename = os.path.join(self.path, 'qml-example-1.2-RC3.xml')
tmpfile = NamedTemporaryFile().name
catalog = readQuakeML(filename)
self.assertTrue(len(catalog), 1)
writeQuakeML(catalog, tmpfile)
# Read file again. Avoid the (legit) warning about the already used
# resource identifiers.
with warnings.catch_warnings(record=True):
warnings.simplefilter("ignore")
catalog2 = readQuakeML(tmpfile)
self.assertTrue(len(catalog2), 1)
# clean up
os.remove(tmpfile)
def test_readEvents(self):
"""
Tests reading a QuakeML document via readEvents.
skipIfPython25 due to the use of the warnings context manager.
"""
filename = os.path.join(self.path, 'neries_events.xml')
tmpfile = NamedTemporaryFile().name
catalog = readEvents(filename)
self.assertTrue(len(catalog), 3)
catalog.write(tmpfile, format='QUAKEML')
# Read file again. Avoid the (legit) warning about the already used
# resource identifiers.
with warnings.catch_warnings(record=True):
warnings.simplefilter("ignore")
catalog2 = readEvents(tmpfile)
self.assertTrue(len(catalog2), 3)
# clean up
os.remove(tmpfile)
def test_read_and_write_scardec_from_open_files(self):
"""
Tests that reading and writing a SCARDEC file does not change
anything.
This time it tests reading from and writing to open files.
"""
filename = os.path.join(self.datapath, "test.scardec")
with open(filename, "rb") as fh:
data = fh.read()
fh.seek(0, 0)
cat = obspy.read_events(fh)
with NamedTemporaryFile() as tf:
# raises two UserWarnings
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always', UserWarning)
cat.write(tf, format="SCARDEC")
tf.seek(0, 0)
new_data = tf.read()
self.assertEqual(len(w), 2)
self.assertEqual(w[0].category, UserWarning)
self.assertIn('No moment wave magnitude found', str(w[0]))
self.assertEqual(w[1].category, UserWarning)
self.assertIn('No derived origin attached', str(w[1]))
# Test file header
self.assertEqual(data.decode().splitlines()[0:2],
new_data.decode().splitlines()[0:2])
for line_data, line_new in zip(data.decode().splitlines()[2:],
new_data.decode().splitlines()[2:]):
# Compare time stamps
self.assertTrue(
np.allclose(float(line_data.split()[0]),
float(line_new.split()[0])))
# Compare moment rate values
self.assertTrue(
np.allclose(float(line_data.split()[1]),
float(line_new.split()[1])))
def test_IRIS_example_queries_event(self):
"""
Tests the (sometimes modified) example queries given on the IRIS
web page.
"""
client = self.client
queries = [
dict(eventid=609301),
dict(starttime=UTCDateTime("2001-01-07T01:00:00"),
endtime=UTCDateTime("2001-01-07T01:05:00"),
catalog="ISC"),
dict(starttime=UTCDateTime("2001-01-07T14:00:00"),
endtime=UTCDateTime("2001-01-08T00:00:00"),
minlatitude=15,
maxlatitude=40,
minlongitude=-170,
maxlongitude=170,
includeallmagnitudes=True,
minmagnitude=4,
orderby="magnitude"),
]
result_files = [
"events_by_eventid.xml",
"events_by_time.xml",
"events_by_misc.xml",
]
for query, filename in zip(queries, result_files):
file_ = os.path.join(self.datapath, filename)
# query["filename"] = file_
got = client.get_events(**query)
expected = read_events(file_)
self.assertEqual(got, expected, failmsg(got, expected))
# test output to file
with NamedTemporaryFile() as tf:
client.get_events(filename=tf.name, **query)
with open(tf.name, 'rb') as fh:
got = fh.read()
with open(file_, 'rb') as fh:
expected = fh.read()
self.assertEqual(got, expected,
filename + '\n' + failmsg(got, expected))
def test_read_and_write_scardec_from_files(self):
"""
Tests that reading and writing a SCARDECfile does not change
anything.
Note: The test file is not one from the catalogue, since it was
impossible to recreate the number formatting. Therefore, the test
file has been created with ObsPy, but was manually checked to be
consistent with the original file
"""
filename = os.path.join(self.datapath, "test.scardec")
with open(filename, "rb") as fh:
data = fh.read()
cat = obspy.read_events(filename)
with NamedTemporaryFile() as tf:
temp_filename = tf.name
try:
cat.write(temp_filename, format="SCARDEC")
with open(temp_filename, "rb") as fh:
new_data = fh.read()
finally:
try:
os.remove(temp_filename)
except:
pass
# Test file header
self.assertEqual(data.decode().splitlines()[0:2],
new_data.decode().splitlines()[0:2])
for line_data, line_new in zip(data.decode().splitlines()[2:],
new_data.decode().splitlines()[2:]):
# Compare time stamps
self.assertTrue(
np.allclose(float(line_data.split()[0]),
float(line_new.split()[0])))
# Compare moment rate values
self.assertTrue(
np.allclose(float(line_data.split()[1]),
float(line_new.split()[1])))
def test_read_and_write_cmtsolution_from_open_files(self):
"""
Tests that reading and writing a CMTSOLUTION file does not change
anything.
This time it tests reading from and writing to open files.
"""
filename = os.path.join(self.datapath, "CMTSOLUTION")
with open(filename, "rb") as fh:
data = fh.read()
fh.seek(0, 0)
cat = obspy.read_events(fh)
with NamedTemporaryFile() as tf:
cat.write(tf, format="CMTSOLUTION")
tf.seek(0, 0)
new_data = tf.read()
self.assertEqual(data.decode().splitlines(),
new_data.decode().splitlines())
def test_plotMultipleTraces(self):
"""
Plots multiple traces underneath.
"""
# 1 trace
st = read()[0]
with NamedTemporaryFile(suffix='.png') as tf:
st.plot(outfile=tf.name, automerge=False)
expected_image = os.path.join(self.path, 'waveform_1_trace.png')
compare_images(tf.name, expected_image, 0.001)
# 3 traces
st = read()
with NamedTemporaryFile(suffix='.png') as tf:
st.plot(outfile=tf.name, automerge=False)
expected_image = os.path.join(self.path, 'waveform_3_traces.png')
compare_images(tf.name, expected_image, 0.001)
# 5 traces
st = st[1] * 5
with NamedTemporaryFile(suffix='.png') as tf:
st.plot(outfile=tf.name, automerge=False)
expected_image = os.path.join(self.path, 'waveform_5_traces.png')
compare_images(tf.name, expected_image, 0.001)
# 10 traces
st = st[1] * 10
with NamedTemporaryFile(suffix='.png') as tf:
st.plot(outfile=tf.name, automerge=False)
expected_image = os.path.join(self.path, 'waveform_10_traces.png')
compare_images(tf.name, expected_image, 0.001)
# 10 traces - huge numbers
st = st[1] * 10
for i, tr in enumerate(st):
# scale data to have huge numbers
st[i].data = tr.data * 10**i
with NamedTemporaryFile(suffix='.png') as tf:
st.plot(outfile=tf.name, automerge=False, equal_scale=False)
expected_image = os.path.join(self.path,
'waveform_10_traces_huge.png')
compare_images(tf.name, expected_image, 0.001)
# 10 traces - tiny numbers
st = st[1] * 10
for i, tr in enumerate(st):
# scale data to have huge numbers
st[i].data = tr.data / (10**i)
with NamedTemporaryFile(suffix='.png') as tf:
st.plot(outfile=tf.name, automerge=False, equal_scale=False)
expected_image = os.path.join(self.path,
'waveform_10_traces_tiny.png')
compare_images(tf.name, expected_image, 0.001)
def test_ppsd_save_and_load_npz(self):
"""
Test PPSD.load_npz() and PPSD.save_npz()
"""
_, paz = _get_sample_data()
ppsd = _get_ppsd()
# save results to npz file
with NamedTemporaryFile(suffix=".npz") as tf:
filename = tf.name
# test saving and loading an uncompressed file
ppsd.save_npz(filename)
ppsd_loaded = PPSD.load_npz(filename, metadata=paz)
for key in PPSD.NPZ_STORE_KEYS:
if isinstance(getattr(ppsd, key), np.ndarray) or \
key == '_binned_psds':
np.testing.assert_equal(getattr(ppsd, key),
getattr(ppsd_loaded, key))
else:
self.assertEqual(getattr(ppsd, key), getattr(ppsd_loaded, key))
def test_more_than_three_mags(self):
cat = Catalog()
cat += full_test_event()
cat[0].magnitudes.append(
Magnitude(mag=0.9,
magnitude_type='MS',
creation_info=CreationInfo('TES'),
origin_id=cat[0].origins[0].resource_id))
with NamedTemporaryFile(suffix='.out') as tf:
# raises UserWarning: mb is not convertible
with warnings.catch_warnings():
warnings.simplefilter('ignore', UserWarning)
cat.write(tf.name, format='nordic')
# raises "UserWarning: AIN in header, currently unsupported"
with warnings.catch_warnings():
warnings.simplefilter('ignore', UserWarning)
cat_back = read_events(tf.name)
for event_1, event_2 in zip(cat, cat_back):
self.assertTrue(
len(event_1.magnitudes) == len(event_2.magnitudes))
_assert_similarity(event_1, event_2)
def test_overlap_fire_testing(self):
"""
Fire tests at a rapid rate to test the overlap function
Rapid overlap testing. Create the following stream:
0 -- 1 -- 2 -- 3 -- 4 -- 5 -- 6 --
3 -- 4 -- 5 -- 6 -- 7 -- 8 -- 9 -- 10 --
8 -- 9 -- 10 -- 11 --
And shoot as many strange windows, check if gaps are calculated
correctly. Add your own!
"""
tr_1 = obspy.Trace(data=np.arange(7, dtype=np.int32),
header={"starttime": obspy.UTCDateTime(0)})
tr_2 = obspy.Trace(data=np.arange(8, dtype=np.int32),
header={"starttime": obspy.UTCDateTime(3)})
tr_3 = obspy.Trace(data=np.arange(4, dtype=np.int32),
header={"starttime": obspy.UTCDateTime(7.5)})
st = obspy.Stream(traces=[tr_1, tr_2, tr_3])
with NamedTemporaryFile() as tf:
st.write(tf.name, format="mseed")
# Supplementary function to test overlaps rapidly with varying
# start and endtimes
def _rapid_overlap_testing(start, end):
md = MSEEDMetadata(files=[tf.name],
starttime=obspy.UTCDateTime(start),
endtime=obspy.UTCDateTime(end))
return md.meta['sum_overlaps']
self.assertTrue(_rapid_overlap_testing(0, 12) == 7.5)
self.assertTrue(_rapid_overlap_testing(3, 7) == 4.0)
self.assertTrue(_rapid_overlap_testing(3, 5.5) == 2.5)
self.assertTrue(_rapid_overlap_testing(4.5, 5.5) == 1.0)
self.assertTrue(_rapid_overlap_testing(2, 5.25) == 2.25)
self.assertTrue(_rapid_overlap_testing(2, 3) == 0.0)
self.assertTrue(_rapid_overlap_testing(2, 3.1) == 0.1)
self.assertTrue(_rapid_overlap_testing(7, 9) == 1.5)
self.assertTrue(_rapid_overlap_testing(6.9, 9) == 1.6)
self.assertTrue(_rapid_overlap_testing(4.30, 9) == 4.2)
self.assertTrue(_rapid_overlap_testing(5.20, 9000) == 5.3)
def test_write_amplitude_time_window(self):
"""
Tests writing an QuakeML Amplitude with TimeWindow.
"""
filename = os.path.join(self.path, "qml-example-1.2-RC3.xml")
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
cat = _read_quakeml(filename)
self.assertEqual(len(w), 0)
with NamedTemporaryFile() as tf:
tmpfile = tf.name
cat.write(tmpfile, format='QUAKEML')
with open(tmpfile, "rb") as fh:
lines = fh.readlines()
firstline = 45
while b"<amplitude " not in lines[firstline]:
firstline += 1
got = [lines[i_].strip()
for i_ in range(firstline, firstline + 13)]
expected = [
b'<amplitude publicID="smi:nz.org.geonet/event/2806038g/'
b'amplitude/1/modified">',
b'<genericAmplitude>',
b'<value>1e-08</value>',
b'</genericAmplitude>',
b'<type>A</type>',
b'<category>point</category>',
b'<unit>m/s</unit>',
b'<timeWindow>',
b'<reference>2007-10-10T14:40:39.055000Z</reference>',
b'<begin>0.0</begin>',
b'<end>0.51424</end>',
b'</timeWindow>',
b'</amplitude>']
self.assertEqual(got, expected)
def test_plotAzimSection(self):
"""
Tests plotting 10 in a azimuthal distant section
"""
start = UTCDateTime(0)
st = Stream()
for _i in range(10):
st += self._createStream(start, start + 3600, 100)
st[-1].stats.coordinates = AttribDict({
'latitude': _i,
'longitude': _i
})
# create and compare image
with NamedTemporaryFile(suffix='.png') as tf:
st.plot(outfile=tf.name,
type='section',
dist_degree=True,
ev_coord=(0.0, 0.0))
# compare images
expected_image = os.path.join(self.path,
'waveform_azim_section.png')
compare_images(tf.name, expected_image, 0.001)
def test_write_with_extra_tags_namespace_redef(self):
"""
Tests the exceptions are raised when namespaces
are redefined.
"""
filename = os.path.join(
self.data_dir, "stationxml_with_availability.xml")
# read the StationXML with availability
inv = obspy.read_inventory(filename)
with NamedTemporaryFile() as tf:
# manually add custom namespace definition
tmpfile = tf.name
# assert that namespace prefix of xsi raises ValueError
mynsmap = {'xsi': 'http://bad.custom.ns/'}
self.assertRaises(
ValueError, inv.write, path_or_file_object=tmpfile,
format="STATIONXML", nsmap=mynsmap)
# assert that namespace prefix of None raises ValueError
mynsmap = {None: 'http://bad.custom.ns/'}
self.assertRaises(
ValueError, inv.write, path_or_file_object=tmpfile,
format="STATIONXML", nsmap=mynsmap)
def test_deepcopy(self):
"""
Test for issue #689: deepcopy did not work for segy. In order to
avoid complicated code to find test data for each waveform pluging,
which read OK and have no errors we simply test by first writing
the waveform and then reading it in. Thus test is limited to
formats which we can also write.
"""
# find all plugins with both read and write method
formats_write = \
set(_get_default_eps('obspy.plugin.waveform', 'writeFormat'))
formats_read = \
set(_get_default_eps('obspy.plugin.waveform', 'readFormat'))
formats = set.intersection(formats_write, formats_read)
stream_orig = read()
for format in formats:
# TODO: these formats error in read and writing, not in
# deepcopy
if format in ('SAC', 'SACXY', 'SEG2', 'Q', 'WAV'):
continue
stream = deepcopy(stream_orig)
# set some data
dt = np.float32
if format in ('GSE2', 'MSEED'):
dt = np.int32
for tr in stream:
tr.data = np.arange(tr.stats.npts).astype(dt)
with NamedTemporaryFile() as tf:
tmpfile = tf.name
with warnings.catch_warnings():
warnings.simplefilter("ignore")
stream.write(format=format, filename=tmpfile)
st = read(tmpfile, format=format)
st.sort()
st_deepcopy = deepcopy(st)
st_deepcopy.sort()
msg = "Error in wavform format=%s" % format
self.assertEqual(str(st), str(st_deepcopy), msg=msg)
def evalresp(t_samp, nfft, filename, date, station='*', channel='*',
network='*', locid='*', units="VEL", start_stage=-1, stop_stage=0, freq=False,
debug=False):
"""
Use the evalresp library to extract instrument response
information from a SEED RESP-file. To restrict the response to the
instrument the start and stop stages can be specified here.
:type t_samp: float
:param t_samp: Sampling interval in seconds
:type nfft: int
:param nfft: Number of FFT points of signal which needs correction
:type filename: str (or open file like object)
:param filename: SEED RESP-filename or open file like object with RESP
information. Any object that provides a read() method will be
considered to be a file like object.
:type date: UTCDateTime
:param date: Date of interest
:type station: str
:param station: Station id
:type channel: str
:param channel: Channel id
:type network: str
:param network: Network id
:type locid: str
:param locid: Location id
:type units: str
:param units: Units to return response in. Can be either DIS, VEL or ACC
:type start_stage: int
:param start_stage: integer stage numbers of start stage (<0 causes
default evalresp bahaviour).
:type stop_stage: int
:param stop_stage: integer stage numbers of stop stage
:type debug: bool
:param debug: Verbose output to stdout. Disabled by default.
:rtype: numpy.ndarray complex128
:return: Frequency response from SEED RESP-file of length nfft
"""
if isinstance(filename, basestring):
with open(filename, 'rb') as fh:
data = fh.read()
elif hasattr(filename, 'read'):
data = filename.read()
# evalresp needs files with correct line separators depending on OS
fh = NamedTemporaryFile()
#with NamedTemporaryFile() as fh:
if 1:
tempfile = fh.name
fh.write(os.linesep.join(data.splitlines()))
fh.close()
fy = 1 / (t_samp * 2.0)
# start at zero to get zero for offset/ DC of fft
freqs = np.linspace(0, fy, nfft // 2 + 1)
start_stage_c = C.c_int(start_stage)
stop_stage_c = C.c_int(stop_stage)
stdio_flag = C.c_int(0)
sta = C.create_string_buffer(station)
cha = C.create_string_buffer(channel)
net = C.create_string_buffer(network)
locid = C.create_string_buffer(locid)
unts = C.create_string_buffer(units)
if debug:
vbs = C.create_string_buffer("-v")
else:
vbs = C.create_string_buffer("")
rtyp = C.create_string_buffer("CS")
datime = C.create_string_buffer(date.formatSEED())
fn = C.create_string_buffer(tempfile)
nfreqs = C.c_int(freqs.shape[0])
res = clibevresp.evresp(sta, cha, net, locid, datime, unts, fn,
freqs, nfreqs, rtyp, vbs, start_stage_c,
stop_stage_c, stdio_flag, C.c_int(0))
# optimizing performance, see
# http://wiki.python.org/moin/PythonSpeed/PerformanceTips
nfreqs, rfreqs, rvec = res[0].nfreqs, res[0].freqs, res[0].rvec
h = np.empty(nfreqs, dtype='complex128')
f = np.empty(nfreqs, dtype='float64')
for i in xrange(nfreqs):
h[i] = rvec[i].real + rvec[i].imag * 1j
f[i] = rfreqs[i]
clibevresp.free_response(res)
del nfreqs, rfreqs, rvec, res
if freq:
return h, f
return h
def evalresp(t_samp, nfft, filename, date, station='*', channel='*',
network='*', locid='*', units="VEL", freq=False,
debug=False):
"""
Use the evalresp library to extract instrument response
information from a SEED RESP-file.
:type t_samp: float
:param t_samp: Sampling interval in seconds
:type nfft: int
:param nfft: Number of FFT points of signal which needs correction
:type filename: str
:param filename: SEED RESP-filename or content of RESP file
:type date: UTCDateTime
:param date: Date of interest
:type station: str
:param station: Station id
:type channel: str
:param channel: Channel id
:type network: str
:param network: Network id
:type locid: str
:param locid: Location id
:type units: str
:param units: Units to return response in. Can be either DIS, VEL or ACC
:type debug: bool
:param debug: Verbose output to stdout. Disabled by default.
:rtype: numpy.ndarray complex128
:return: Frequency response from SEED RESP-file of length nfft
"""
# evalresp needs files with correct line separators depending on OS
data = open(filename, 'rb').read()
fh = NamedTemporaryFile()
tempfile = fh.name
fh.write(os.linesep.join(data.splitlines()))
fh.close()
fy = 1 / (t_samp * 2.0)
# start at zero to get zero for offset/ DC of fft
freqs = np.linspace(0, fy, nfft // 2 + 1)
start_stage = C.c_int(-1)
stop_stage = C.c_int(0)
stdio_flag = C.c_int(0)
sta = C.create_string_buffer(station)
cha = C.create_string_buffer(channel)
net = C.create_string_buffer(network)
locid = C.create_string_buffer(locid)
unts = C.create_string_buffer(units)
if debug:
vbs = C.create_string_buffer("-v")
else:
vbs = C.create_string_buffer("")
rtyp = C.create_string_buffer("CS")
datime = C.create_string_buffer("%d,%3d" % (date.year, date.julday))
fn = C.create_string_buffer(tempfile)
nfreqs = C.c_int(freqs.shape[0])
res = clibevresp.evresp(sta, cha, net, locid, datime, unts, fn,
freqs, nfreqs, rtyp, vbs, start_stage,
stop_stage, stdio_flag, C.c_int(0))
# optimizing performance, see
# http://wiki.python.org/moin/PythonSpeed/PerformanceTips
nfreqs, rfreqs, rvec = res[0].nfreqs, res[0].freqs, res[0].rvec
h = np.empty(nfreqs, dtype='complex128')
f = np.empty(nfreqs, dtype='float64')
for i in xrange(nfreqs):
h[i] = rvec[i].real + rvec[i].imag * 1j
f[i] = rfreqs[i]
clibevresp.free_response(res)
del nfreqs, rfreqs, rvec, res
# delete temporary file
try:
os.remove(tempfile)
except:
pass
if freq:
return h, f
return h
