def test_station5():
homedir = os.path.dirname(os.path.abspath(__file__))
event = 'Calexico'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
inputfile = os.path.join(datadir, 'stationlist_dat.xml')
dyfifile = os.path.join(datadir, 'ciim3_dat.xml')
xmlfiles = [inputfile, dyfifile]
stations1 = StationList.loadFromXML(xmlfiles, ":memory:")
#
# Load the data more than once to exercise the code that handles
# repeated entries.
#
xmlfiles = [inputfile, inputfile, dyfifile, dyfifile]
stations2 = StationList.loadFromXML(xmlfiles, ":memory:")
df1 = stations1.getStationDictionary(instrumented=True)
df2 = stations2.getStationDictionary(instrumented=True)
compare_dataframes(df1, df2)
def test_station5():
homedir = os.path.dirname(os.path.abspath(__file__))
event = 'Calexico'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
inputfile = os.path.join(datadir, 'stationlist_dat.xml')
dyfifile = os.path.join(datadir, 'ciim3_dat.xml')
xmlfiles = [inputfile, dyfifile]
stations1 = StationList.loadFromXML(xmlfiles, ":memory:")
#
# Load the data more than once to exercise the code that handles
# repeated entries.
#
xmlfiles = [inputfile, inputfile, dyfifile, dyfifile]
stations2 = StationList.loadFromXML(xmlfiles, ":memory:")
df1, _ = stations1.getStationDictionary(instrumented=True)
df2, _ = stations2.getStationDictionary(instrumented=True)
compare_dataframes(df1, df2)
def setStationData(self, datafiles):
"""
Insert observed ground motion data into the container.
Args:
datafiles (str): Path to an XML-formatted file containing ground
motion observations, (macroseismic or instrumented).
"""
station = StationList.loadFromXML(datafiles)
self.setStationList(station)
def setStationData(self, datafiles):
"""
Insert observed ground motion data into the container.
Args:
datafiles (str): Path to an XML-formatted file containing ground
motion observations, (macroseismic or instrumented).
"""
station = StationList.loadFromXML(datafiles)
self.setStationList(station)
def test_station2():
#
# Test the wenchuan data
#
homedir = os.path.dirname(os.path.abspath(__file__))
event = 'wenchuan'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
inputfile = os.path.join(datadir, 'stationlist.xml')
xmlfiles = [inputfile]
stations = StationList.loadFromXML(xmlfiles, ":memory:")
df1, _ = stations.getStationDictionary(instrumented=True)
df2, _ = stations.getStationDictionary(instrumented=False)
ppath = os.path.abspath(os.path.join(datadir, '..', 'database',
'test3.pickle'))
if SAVE:
ldf = [df1, df2]
with open(ppath, 'wb') as f:
pickle.dump(ldf, f, pickle.HIGHEST_PROTOCOL)
else:
with open(ppath, 'rb') as f:
ldf = pickle.load(f)
saved_df1 = ldf[0]
saved_df2 = ldf[1]
compare_dataframes(saved_df1, df1)
compare_dataframes(saved_df2, df2)
#
# Dump the database to SQL and then restore it to a new
# StationList object. Compare dataframes.
#
sql = stations.dumpToSQL()
stations2 = StationList.loadFromSQL(sql)
df1, _ = stations2.getStationDictionary(instrumented=True)
df2, _ = stations2.getStationDictionary(instrumented=False)
compare_dataframes(saved_df1, df1)
compare_dataframes(saved_df2, df2)
def test_station2():
#
# Test the wenchuan data
#
homedir = os.path.dirname(os.path.abspath(__file__))
event = 'wenchuan'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
inputfile = os.path.join(datadir, 'stationlist.xml')
xmlfiles = [inputfile]
stations = StationList.loadFromXML(xmlfiles, ":memory:")
df1 = stations.getStationDictionary(instrumented=True)
df2 = stations.getStationDictionary(instrumented=False)
ppath = os.path.abspath(os.path.join(datadir, '..', 'database',
'test3.pickle'))
if SAVE:
ldf = [df1, df2]
with open(ppath, 'wb') as f:
pickle.dump(ldf, f, pickle.HIGHEST_PROTOCOL)
else:
with open(ppath, 'rb') as f:
ldf = pickle.load(f)
saved_df1 = ldf[0]
saved_df2 = ldf[1]
compare_dataframes(saved_df1, df1)
compare_dataframes(saved_df2, df2)
#
# Dump the database to SQL and then restore it to a new
# StationList object. Compare dataframes.
#
sql = stations.dumpToSQL()
stations2 = StationList.loadFromSQL(sql)
df1 = stations2.getStationDictionary(instrumented=True)
df2 = stations2.getStationDictionary(instrumented=False)
compare_dataframes(saved_df1, df1)
compare_dataframes(saved_df2, df2)
def test_station4():
homedir = os.path.dirname(os.path.abspath(__file__))
event = 'northridge'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
dyfifile = os.path.join(datadir, 'dyfi_dat.xml')
xmlfiles = [dyfifile]
stations = StationList.loadFromXML(xmlfiles, ":memory:")
df1, _ = stations.getStationDictionary(instrumented=True) # noqa
df2, _ = stations.getStationDictionary(instrumented=False) # noqa
assert df1 is None
def test_station4():
homedir = os.path.dirname(os.path.abspath(__file__))
event = 'northridge'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
dyfifile = os.path.join(datadir, 'dyfi_dat.xml')
xmlfiles = [dyfifile]
stations = StationList.loadFromXML(xmlfiles, ":memory:")
df1 = stations.getStationDictionary(instrumented=True) # noqa
df2 = stations.getStationDictionary(instrumented=False) # noqa
assert df1 is None
def test_station3():
#
# Exercise the geojson code. Can't really compare it to anything
# because the ordering is scrambled by the hashes in the XML
# parsing stage. Once (if) we institute a loadFromJSON() method, we
# can do a comparison.
#
homedir = os.path.dirname(os.path.abspath(__file__))
event = 'wenchuan'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
inputfile = os.path.join(datadir, 'stationlist.xml')
xmlfiles = [inputfile]
stations = StationList.loadFromXML(xmlfiles, ":memory:")
myjson = stations.getGeoJson() # noqa
def test_station3():
#
# Exercise the geojson code. Can't really compare it to anything
# because the ordering is scrambled by the hashes in the XML
# parsing stage. Once (if) we institute a loadFromJSON() method, we
# can do a comparison.
#
homedir = os.path.dirname(os.path.abspath(__file__))
event = 'wenchuan'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
inputfile = os.path.join(datadir, 'stationlist.xml')
xmlfiles = [inputfile]
stations = StationList.loadFromXML(xmlfiles, ":memory:")
myjson = stations.getGeoJson() # noqa
def test_station():
homedir = os.path.dirname(os.path.abspath(__file__))
#
# First test the Calexico data on its own
#
event = 'Calexico'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
inputfile = os.path.join(datadir, 'stationlist_dat.xml')
dyfifile = os.path.join(datadir, 'ciim3_dat.xml')
xmlfiles = [inputfile, dyfifile]
stations = StationList.loadFromXML(xmlfiles, ":memory:")
df1, _ = stations.getStationDictionary(instrumented=True)
df2, _ = stations.getStationDictionary(instrumented=False)
ppath = os.path.abspath(os.path.join(datadir, '..', 'database',
'test1.pickle'))
if SAVE:
ldf = [df1, df2]
with open(ppath, 'wb') as f:
pickle.dump(ldf, f, pickle.HIGHEST_PROTOCOL)
else:
with open(ppath, 'rb') as f:
ldf = pickle.load(f)
saved_df1 = ldf[0]
saved_df2 = ldf[1]
compare_dataframes(saved_df1, df1)
compare_dataframes(saved_df2, df2)
#
# Should at least hit this code
#
imtlist = stations.getIMTtypes()
assert 'PGA' in imtlist
assert 'PGV' in imtlist
#
# Add the Northridge data to the Calexico data to test
# addData()
#
event = 'northridge'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
inputfile = os.path.join(datadir, 'hist_dat.xml')
dyfifile = os.path.join(datadir, 'dyfi_dat.xml')
xmlfiles = [inputfile, dyfifile]
stations = stations.addData(xmlfiles)
df1, _ = stations.getStationDictionary(instrumented=True)
df2, _ = stations.getStationDictionary(instrumented=False)
ppath = os.path.abspath(os.path.join(datadir, '..', 'database',
'test2.pickle'))
if SAVE:
ldf = [df1, df2]
with open(ppath, 'wb') as f:
pickle.dump(ldf, f, pickle.HIGHEST_PROTOCOL)
else:
with open(ppath, 'rb') as f:
ldf = pickle.load(f)
saved_df1 = ldf[0]
saved_df2 = ldf[1]
compare_dataframes(saved_df1, df1)
compare_dataframes(saved_df2, df2)
def test_station():
homedir = os.path.dirname(os.path.abspath(__file__))
#
# First test the Calexico data on its own
#
event = 'Calexico'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
inputfile = os.path.join(datadir, 'stationlist_dat.xml')
dyfifile = os.path.join(datadir, 'ciim3_dat.xml')
xmlfiles = [inputfile, dyfifile]
stations = StationList.loadFromXML(xmlfiles, ":memory:")
df1 = stations.getStationDictionary(instrumented=True)
df2 = stations.getStationDictionary(instrumented=False)
ppath = os.path.abspath(os.path.join(datadir, '..', 'database',
'test1.pickle'))
if SAVE:
ldf = [df1, df2]
with open(ppath, 'wb') as f:
pickle.dump(ldf, f, pickle.HIGHEST_PROTOCOL)
else:
with open(ppath, 'rb') as f:
ldf = pickle.load(f)
saved_df1 = ldf[0]
saved_df2 = ldf[1]
compare_dataframes(saved_df1, df1)
compare_dataframes(saved_df2, df2)
#
# Should at least hit this code
#
imtlist = stations.getIMTtypes()
assert 'PGA' in imtlist
assert 'PGV' in imtlist
#
# Add the Northridge data to the Calexico data to test
# addData()
#
event = 'northridge'
datadir = os.path.abspath(os.path.join(homedir, 'station_data'))
datadir = os.path.abspath(os.path.join(datadir, event, 'input'))
inputfile = os.path.join(datadir, 'hist_dat.xml')
dyfifile = os.path.join(datadir, 'dyfi_dat.xml')
xmlfiles = [inputfile, dyfifile]
stations = stations.addData(xmlfiles)
df1 = stations.getStationDictionary(instrumented=True)
df2 = stations.getStationDictionary(instrumented=False)
ppath = os.path.abspath(os.path.join(datadir, '..', 'database',
'test2.pickle'))
if SAVE:
ldf = [df1, df2]
with open(ppath, 'wb') as f:
pickle.dump(ldf, f, pickle.HIGHEST_PROTOCOL)
else:
with open(ppath, 'rb') as f:
ldf = pickle.load(f)
saved_df1 = ldf[0]
saved_df2 = ldf[1]
compare_dataframes(saved_df1, df1)
compare_dataframes(saved_df2, df2)