def test():
homedir = os.path.dirname(os.path.abspath(
__file__)) # where is this script?
fatfile = os.path.join(homedir, '..', 'data', 'fatality.xml')
ecofile = os.path.join(homedir, '..', 'data', 'economy.xml')
cityfile = os.path.join(homedir, '..', 'data', 'cities1000.txt')
event = 'northridge'
shakefile = os.path.join(homedir, '..', 'data',
'eventdata', event, '%s_grid.xml' % event)
popfile = os.path.join(homedir, '..', 'data',
'eventdata', event, '%s_gpw.flt' % event)
isofile = os.path.join(homedir, '..', 'data',
'eventdata', event, '%s_isogrid.bil' % event)
urbanfile = os.path.join(homedir, '..', 'data',
'eventdata', 'northridge', 'northridge_urban.bil')
oceanfile = os.path.join(
homedir, '..', 'data', 'eventdata', 'northridge', 'northridge_ocean.json')
oceangridfile = os.path.join(
homedir, '..', 'data', 'eventdata', 'northridge', 'northridge_ocean.bil')
timezonefile = os.path.join(
homedir, '..', 'data', 'eventdata', 'northridge', 'northridge_timezone.shp')
invfile = os.path.join(homedir, '..', 'data', 'semi_inventory.hdf')
colfile = os.path.join(homedir, '..', 'data', 'semi_collapse_mmi.hdf')
casfile = os.path.join(homedir, '..', 'data', 'semi_casualty.hdf')
workfile = os.path.join(homedir, '..', 'data', 'semi_workforce.hdf')
tdir = tempfile.mkdtemp()
basename = os.path.join(tdir, 'output')
exp = Exposure(popfile, 2012, isofile)
results = exp.calcExposure(shakefile)
shakegrid = exp.getShakeGrid()
popgrid = exp.getPopulationGrid()
pdffile, pngfile, mapcities = draw_contour(
shakegrid, popgrid, oceanfile, oceangridfile, cityfile, basename)
shutil.rmtree(tdir)
popyear = 2012
shake_tuple = getHeaderData(shakefile)
tsunami = shake_tuple[1]['magnitude'] >= TSUNAMI_MAG_THRESH
semi = SemiEmpiricalFatality.fromDefault()
semi.setGlobalFiles(popfile, popyear, urbanfile, isofile)
semiloss, resfat, nonresfat = semi.getLosses(shakefile)
popgrowth = PopulationGrowth.fromDefault()
econexp = EconExposure(popfile, 2012, isofile)
fatmodel = EmpiricalLoss.fromDefaultFatality()
expobject = Exposure(popfile, 2012, isofile, popgrowth)
expdict = expobject.calcExposure(shakefile)
fatdict = fatmodel.getLosses(expdict)
econexpdict = econexp.calcExposure(shakefile)
ecomodel = EmpiricalLoss.fromDefaultEconomic()
ecodict = ecomodel.getLosses(expdict)
shakegrid = econexp.getShakeGrid()
pagerversion = 1
cities = Cities.loadFromGeoNames(cityfile)
impact1 = '''Red alert level for economic losses. Extensive damage is probable
and the disaster is likely widespread. Estimated economic losses are less
than 1% of GDP of Italy. Past events with this alert level have required
a national or international level response.'''
impact2 = '''Orange alert level for shaking-related fatalities. Significant
casualties are likely.'''
structcomment = '''Overall, the population in this region resides in structures
that are a mix of vulnerable and earthquake resistant construction. The predominant
vulnerable building types are unreinforced brick with mud and mid-rise nonductile
concrete frame with infill construction.'''
histeq = [1, 2, 3]
struct_comment = '''Overall, the population in this region resides
in structures that are resistant to earthquake
shaking, though some vulnerable structures
exist.'''
secondary_comment = '''Recent earthquakes in this area have caused secondary hazards
such as landslides that might have contributed to losses.'''
hist_comment = ''''A magnitude 7.1 earthquake 240 km east of this event struck Reventador: Ecuador
on March 6, 1987 (UTC), with estimated population exposures of 14,000 at intensity VIII and 2,000
at intensity IX or greater, resulting in a reported 5,000 fatalities.'''.replace('\n', '')
location = 'At the top of the world.'
is_released = True
doc = PagerData()
eventcode = shakegrid.getEventDict()['event_id']
versioncode = eventcode
doc.setInputs(shakegrid, timezonefile, pagerversion,
versioncode, eventcode, tsunami, location, is_released)
doc.setExposure(expdict, econexpdict)
doc.setModelResults(fatmodel, ecomodel,
fatdict, ecodict,
semiloss, resfat, nonresfat)
doc.setComments(impact1, impact2, struct_comment,
hist_comment, secondary_comment)
doc.setMapInfo(cityfile, mapcities)
doc.validate()
# let's test the property methods
tdoc(doc, shakegrid, impact1, impact2,
expdict, struct_comment, hist_comment)
# see if we can save this to a bunch of files then read them back in
try:
tdir = tempfile.mkdtemp()
doc.saveToJSON(tdir)
newdoc = PagerData()
newdoc.loadFromJSON(tdir)
tdoc(newdoc, shakegrid, impact1, impact2,
expdict, struct_comment, hist_comment)
# test the xml saving method
xmlfile = doc.saveToLegacyXML(tdir)
except Exception as e:
assert 1 == 2
finally:
shutil.rmtree(tdir)
def test():
homedir = os.path.dirname(os.path.abspath(__file__)) #where is this script?
fatfile = os.path.join(homedir,'..','data','fatality.xml')
ecofile = os.path.join(homedir,'..','data','economy.xml')
cityfile = os.path.join(homedir,'..','data','cities1000.txt')
event = 'northridge'
shakefile = os.path.join(homedir,'..','data','eventdata',event,'%s_grid.xml' % event)
popfile = os.path.join(homedir,'..','data','eventdata',event,'%s_gpw.flt' % event)
isofile = os.path.join(homedir,'..','data','eventdata',event,'%s_isogrid.bil' % event)
urbanfile = os.path.join(homedir,'..','data','eventdata','northridge','northridge_urban.bil')
oceanfile = os.path.join(homedir,'..','data','eventdata','northridge','northridge_ocean.json')
invfile = os.path.join(homedir,'..','data','semi_inventory.hdf')
colfile = os.path.join(homedir,'..','data','semi_collapse_mmi.hdf')
casfile = os.path.join(homedir,'..','data','semi_casualty.hdf')
workfile = os.path.join(homedir,'..','data','semi_workforce.hdf')
tdir = tempfile.mkdtemp()
outfile = os.path.join(tdir,'output.pdf')
pngfile,mapcities = draw_contour(shakefile,popfile,oceanfile,cityfile,outfile,make_png=True)
shutil.rmtree(tdir)
popyear = 2012
semi = SemiEmpiricalFatality.fromDefault()
semi.setGlobalFiles(popfile,popyear,urbanfile,isofile)
semiloss,resfat,nonresfat = semi.getLosses(shakefile)
popgrowth = PopulationGrowth.fromDefault()
econexp = EconExposure(popfile,2012,isofile)
fatmodel = EmpiricalLoss.fromDefaultFatality()
expobject = Exposure(popfile,2012,isofile,popgrowth)
expdict = expobject.calcExposure(shakefile)
fatdict = fatmodel.getLosses(expdict)
econexpdict = econexp.calcExposure(shakefile)
ecomodel = EmpiricalLoss.fromDefaultEconomic()
ecodict = ecomodel.getLosses(expdict)
shakegrid = econexp.getShakeGrid()
pagerversion = 1
cities = Cities.loadFromGeoNames(cityfile)
impact1 = '''Red alert level for economic losses. Extensive damage is probable
and the disaster is likely widespread. Estimated economic losses are less
than 1% of GDP of Italy. Past events with this alert level have required
a national or international level response.'''
impact2 = '''Orange alert level for shaking-related fatalities. Significant
casualties are likely.'''
structcomment = '''Overall, the population in this region resides in structures
that are a mix of vulnerable and earthquake resistant construction. The predominant
vulnerable building types are unreinforced brick with mud and mid-rise nonductile
concrete frame with infill construction.'''
histeq = [1,2,3]
struct_comment = '''Overall, the population in this region resides
in structures that are resistant to earthquake
shaking, though some vulnerable structures
exist.'''
secondary_comment = '''Recent earthquakes in this area have caused secondary hazards
such as landslides that might have contributed to losses.'''
hist_comment = ''''A magnitude 7.1 earthquake 240 km east of this event struck Reventador: Ecuador
on March 6, 1987 (UTC), with estimated population exposures of 14,000 at intensity VIII and 2,000
at intensity IX or greater, resulting in a reported 5,000 fatalities.'''.replace('\n','')
doc = PagerData()
doc.setInputs(shakegrid,pagerversion,shakegrid.getEventDict()['event_id'])
doc.setExposure(expdict,econexpdict)
doc.setModelResults(fatmodel,ecomodel,
fatdict,ecodict,
semiloss,resfat,nonresfat)
doc.setComments(impact1,impact2,struct_comment,hist_comment,secondary_comment)
doc.setMapInfo(cityfile,mapcities)
doc.validate()
eventinfo = doc.getEventInfo()
assert eventinfo['mag'] == shakegrid.getEventDict()['magnitude']
imp1,imp2 = doc.getImpactComments()
assert imp1 == impact1 and imp2 == impact2
version = doc.getSoftwareVersion()
elapsed = doc.getElapsed()
exp = doc.getTotalExposure()
assert np.isclose(np.array(exp),expdict['TotalExposure']).all()
hist_table = doc.getHistoricalTable()
assert hist_table[0]['EventID'] == '199206281505'
scomm = doc.getStructureComment()
assert scomm == struct_comment
hcomm = doc.getHistoricalComment()
assert hcomm == hist_comment
citytable = doc.getCityTable()
assert citytable.iloc[0]['name'] == 'Santa Clarita'
summary = doc.getSummaryAlert()
assert summary == 'yellow'
def test():
event = 'northridge'
homedir = os.path.dirname(
os.path.abspath(__file__)) # where is this script?
shakefile = os.path.join(homedir, '..', 'data', 'eventdata', event,
'%s_grid.xml' % event)
popfile = os.path.join(homedir, '..', 'data', 'eventdata', event,
'%s_gpw.flt' % event)
isofile = os.path.join(homedir, '..', 'data', 'eventdata', event,
'%s_isogrid.bil' % event)
shapefile = os.path.join(homedir, '..', 'data', 'eventdata', event,
'City_BoundariesWGS84', 'City_Boundaries.shp')
print('Test loading economic exposure from inputs...')
econexp = EconExposure(popfile, 2012, isofile)
print('Passed loading economic exposure from inputs...')
print('Test loading empirical fatality model from XML file...')
ecomodel = EmpiricalLoss.fromDefaultEconomic()
print('Passed loading empirical fatality model from XML file.')
print('Testing calculating probabilities for standard PAGER ranges...')
expected = {'UK': 6819.883892 * 1e6, 'TotalDollars': 6819.883892 * 1e6}
G = 2.5
probs = ecomodel.getProbabilities(expected, G)
testprobs = {
'0-1': 0.00020696841425738358,
'1-10': 0.0043200811319132086,
'10-100': 0.041085446477813294,
'100-1000': 0.17564981840854255,
'1000-10000': 0.33957681768639003,
'10000-100000': 0.29777890303065313,
'100000-10000000': 0.14138196485040311
}
for key, value in probs.items():
np.testing.assert_almost_equal(value, testprobs[key])
msg = ('Passed combining G values from all countries that '
'contributed to losses...')
print(msg)
print('Test retrieving economic model data from XML file...')
model = ecomodel.getModel('af')
testmodel = LognormalModel('dummy',
9.013810,
0.100000,
4.113200,
alpha=15.065400)
assert model == testmodel
print('Passed retrieving economic model data from XML file.')
print('Testing with known exposures/losses for 1994 Northridge EQ...')
exposure = {
'xf':
np.array([
0, 0, 556171936.807, 718990717350.0, 2.40385709638e+12,
2.47073141687e+12, 1.2576210799e+12, 698888019337.0, 1913733716.16,
0.0
])
}
expodict = ecomodel.getLosses(exposure)
testdict = {'xf': 25945225582}
assert expodict['xf'] == testdict['xf']
msg = ('Passed testing with known exposures/fatalities for '
'1994 Northridge EQ.')
print(msg)
print('Testing calculating total economic losses for Northridge...')
expdict = econexp.calcExposure(shakefile)
ecomodel = EmpiricalLoss.fromDefaultEconomic()
lossdict = ecomodel.getLosses(expdict)
testdict = {'XF': 23172277187}
assert lossdict['XF'] == testdict['XF']
print('Passed calculating total economic losses for Northridge...')
print('Testing creating a economic loss grid...')
mmidata = econexp.getShakeGrid().getLayer('mmi').getData()
popdata = econexp.getEconPopulationGrid().getData()
isodata = econexp.getCountryGrid().getData()
ecogrid = ecomodel.getLossGrid(mmidata, popdata, isodata)
ecosum = 23172275857.094917
assert np.nansum(ecogrid) == ecosum
print('Passed creating a economic loss grid.')
print('Testing assigning economic losses to polygons...')
popdict = econexp.getPopulationGrid().getGeoDict()
shapes = []
f = fiona.open(shapefile, 'r')
for row in f:
shapes.append(row)
f.close()
ecoshapes, toteco = ecomodel.getLossByShapes(mmidata, popdata, isodata,
shapes, popdict)
ecoshapes = sorted(ecoshapes,
key=lambda shape: shape['properties']['dollars_lost'],
reverse=True)
lalosses = 17323352577
for shape in ecoshapes:
if shape['id'] == '312': # Los Angeles
cname = shape['properties']['CITY_NAME']
dollars = shape['properties']['dollars_lost']
assert lalosses == dollars
assert cname == 'Los Angeles'
print('Passed assigning economic losses to polygons...')
def main(pargs, config):
# get the users home directory
homedir = os.path.expanduser("~")
# handle cancel messages
if pargs.cancel:
# we presume that pargs.gridfile in this context is an event ID.
msg = _cancel(pargs.gridfile, config)
print(msg)
return True
# what kind of thing is gridfile?
is_file = os.path.isfile(pargs.gridfile)
is_url, url_gridfile = _is_url(pargs.gridfile)
is_pdl, pdl_gridfile = _check_pdl(pargs.gridfile, config)
if is_file:
gridfile = pargs.gridfile
elif is_url:
gridfile = url_gridfile
elif is_pdl:
gridfile = pdl_gridfile
else:
print("ShakeMap Grid file %s does not exist." % pargs.gridfile)
return False
pager_folder = os.path.join(homedir, config["output_folder"])
pager_archive = os.path.join(homedir, config["archive_folder"])
admin = PagerAdmin(pager_folder, pager_archive)
# stdout will now be logged as INFO, stderr will be logged as WARNING
mail_host = config["mail_hosts"][0]
mail_from = config["mail_from"]
developers = config["developers"]
logfile = os.path.join(pager_folder, "pager.log")
plog = PagerLogger(logfile, developers, mail_from, mail_host, debug=pargs.debug)
logger = plog.getLogger()
try:
eid = None
pager_version = None
# get all the basic event information and print it, if requested
shake_tuple = getHeaderData(gridfile)
eid = shake_tuple[1]["event_id"].lower()
etime = shake_tuple[1]["event_timestamp"]
if not len(eid):
eid = shake_tuple[0]["event_id"].lower()
network = shake_tuple[1]["event_network"].lower()
if network == "":
network = "us"
if not eid.startswith(network):
eid = network + eid
# Create a ComcatInfo object to hopefully tell us a number of things about this event
try:
ccinfo = ComCatInfo(eid)
location = ccinfo.getLocation()
tsunami = ccinfo.getTsunami()
authid, allids = ccinfo.getAssociatedIds()
authsource, othersources = ccinfo.getAssociatedSources()
except: # fail over to what we can determine locally
location = shake_tuple[1]["event_description"]
tsunami = shake_tuple[1]["magnitude"] >= TSUNAMI_MAG_THRESH
authid = eid
authsource = network
allids = []
# location field can be empty (None), which breaks a bunch of things
if location is None:
location = ""
# Check to see if user wanted to override default tsunami criteria
if pargs.tsunami != "auto":
if pargs.tsunami == "on":
tsunami = True
else:
tsunami = False
# check to see if this event is a scenario
is_scenario = False
shakemap_type = shake_tuple[0]["shakemap_event_type"]
if shakemap_type == "SCENARIO":
is_scenario = True
# if event is NOT a scenario and event time is in the future,
# flag the event as a scenario and yell about it.
if etime > datetime.datetime.utcnow():
is_scenario = True
logger.warning(
"Event origin time is in the future! Flagging this as a scenario."
)
if is_scenario:
if re.search("scenario", location.lower()) is None:
location = "Scenario " + location
# create the event directory (if it does not exist), and start logging there
logger.info("Creating event directory")
event_folder = admin.createEventFolder(authid, etime)
# Stop processing if there is a "stop" file in the event folder
stopfile = os.path.join(event_folder, "stop")
if os.path.isfile(stopfile):
fmt = '"stop" file found in %s. Stopping processing, returning with 1.'
logger.info(fmt % (event_folder))
return True
pager_version = get_pager_version(event_folder)
version_folder = os.path.join(event_folder, "version.%03d" % pager_version)
os.makedirs(version_folder)
event_logfile = os.path.join(version_folder, "event.log")
# this will turn off the global rotating log file
# and switch to the one in the version folder.
plog.setVersionHandler(event_logfile)
# Copy the grid.xml file to the version folder
# sometimes (usu when testing) the input grid isn't called grid.xml. Rename it here.
version_grid = os.path.join(version_folder, "grid.xml")
shutil.copyfile(gridfile, version_grid)
# Check to see if the tsunami flag has been previously set
tsunami_toggle = {"on": 1, "off": 0}
tsunami_file = os.path.join(event_folder, "tsunami")
if os.path.isfile(tsunami_file):
tsunami = tsunami_toggle[open(tsunami_file, "rt").read().strip()]
# get the rest of the event info
etime = shake_tuple[1]["event_timestamp"]
elat = shake_tuple[1]["lat"]
elon = shake_tuple[1]["lon"]
emag = shake_tuple[1]["magnitude"]
# get the year of the event
event_year = shake_tuple[1]["event_timestamp"].year
# find the population data collected most closely to the event_year
pop_year, popfile = _get_pop_year(
event_year, config["model_data"]["population_data"]
)
logger.info("Population year: %i Population file: %s\n" % (pop_year, popfile))
# Get exposure results
logger.info("Calculating population exposure.")
isofile = config["model_data"]["country_grid"]
expomodel = Exposure(popfile, pop_year, isofile)
exposure = None
exposure = expomodel.calcExposure(gridfile)
# incidentally grab the country code of the epicenter
numcode = expomodel._isogrid.getValue(elat, elon)
if np.isnan(numcode):
cdict = None
else:
cdict = Country().getCountry(int(numcode))
if cdict is None:
ccode = "UK"
else:
ccode = cdict["ISO2"]
logger.info("Country code at epicenter is %s" % ccode)
# get fatality results, if requested
logger.info("Calculating empirical fatalities.")
fatmodel = EmpiricalLoss.fromDefaultFatality()
fatdict = fatmodel.getLosses(exposure)
# get economic results, if requested
logger.info("Calculating economic exposure.")
econexpmodel = EconExposure(popfile, pop_year, isofile)
ecomodel = EmpiricalLoss.fromDefaultEconomic()
econexposure = econexpmodel.calcExposure(gridfile)
ecodict = ecomodel.getLosses(econexposure)
shakegrid = econexpmodel.getShakeGrid()
# Get semi-empirical losses
logger.info("Calculating semi-empirical fatalities.")
urbanfile = config["model_data"]["urban_rural_grid"]
if not os.path.isfile(urbanfile):
raise PagerException("Urban-rural grid file %s does not exist." % urbanfile)
semi = SemiEmpiricalFatality.fromDefault()
semi.setGlobalFiles(popfile, pop_year, urbanfile, isofile)
semiloss, resfat, nonresfat = semi.getLosses(gridfile)
# get all of the other components of PAGER
logger.info("Getting all comments.")
# get the fatality and economic comments
impact1, impact2 = get_impact_comments(
fatdict, ecodict, econexposure, event_year, ccode
)
# get comment describing vulnerable structures in the region.
struct_comment = get_structure_comment(resfat, nonresfat, semi)
# get the comment describing historic secondary hazards
secondary_comment = get_secondary_comment(elat, elon, emag)
# get the comment describing historical comments in the region
historical_comment = get_historical_comment(elat, elon, emag, exposure, fatdict)
# generate the probability plots
logger.info("Drawing probability plots.")
fat_probs_file, eco_probs_file = _draw_probs(
fatmodel, fatdict, ecomodel, ecodict, version_folder
)
# generate the exposure map
exposure_base = os.path.join(version_folder, "exposure")
logger.info("Generating exposure map...")
oceanfile = config["model_data"]["ocean_vectors"]
oceangrid = config["model_data"]["ocean_grid"]
cityfile = config["model_data"]["city_file"]
borderfile = config["model_data"]["border_vectors"]
shake_grid = expomodel.getShakeGrid()
pop_grid = expomodel.getPopulationGrid()
pdf_file, png_file, mapcities = draw_contour(
shake_grid,
pop_grid,
oceanfile,
oceangrid,
cityfile,
exposure_base,
borderfile,
is_scenario=is_scenario,
)
logger.info("Generated exposure map %s" % pdf_file)
# figure out whether this event has been "released".
is_released = _get_release_status(
pargs,
config,
fatmodel,
fatdict,
ecomodel,
ecodict,
shake_tuple,
event_folder,
)
# Create a data object to encapsulate everything we know about the PAGER
# results, and then serialize that to disk in the form of a number of JSON files.
logger.info("Making PAGER Data object.")
doc = PagerData()
timezone_file = config["model_data"]["timezones_file"]
elapsed = pargs.elapsed
doc.setInputs(
shakegrid,
timezone_file,
pager_version,
shakegrid.getEventDict()["event_id"],
authid,
tsunami,
location,
is_released,
elapsed=elapsed,
)
logger.info("Setting inputs.")
doc.setExposure(exposure, econexposure)
logger.info("Setting exposure.")
doc.setModelResults(
fatmodel, ecomodel, fatdict, ecodict, semiloss, resfat, nonresfat
)
logger.info("Setting comments.")
doc.setComments(
impact1, impact2, struct_comment, historical_comment, secondary_comment
)
logger.info("Setting map info.")
doc.setMapInfo(cityfile, mapcities)
logger.info("Validating.")
doc.validate()
# if we have determined that the event is a scenario (origin time is in the future)
# and the shakemap is not flagged as such, set the shakemap type in the
# pagerdata object to be 'SCENARIO'.
if is_scenario:
doc.setToScenario()
json_folder = os.path.join(version_folder, "json")
os.makedirs(json_folder)
logger.info("Saving output to JSON.")
doc.saveToJSON(json_folder)
logger.info("Saving output to XML.")
doc.saveToLegacyXML(version_folder)
logger.info("Creating onePAGER pdf...")
onepager_pdf, error = create_onepager(doc, version_folder)
if onepager_pdf is None:
raise PagerException("Could not create onePAGER output: \n%s" % error)
# copy the contents.xml file to the version folder
contentsfile = get_data_path("contents.xml")
if contentsfile is None:
raise PagerException("Could not find contents.xml file.")
shutil.copy(contentsfile, version_folder)
# send pdf as attachment to internal team of PAGER users
if not is_released and not is_scenario:
message_pager(config, onepager_pdf, doc)
# run transfer, as appropriate and as specified by config
# the PAGER product eventsource and eventsourcecode should
# match the input ShakeMap settings for these properties.
# This can possibly cause confusion if a regional ShakeMap is
# trumped with one from NEIC, but this should happen less often
# than an NEIC origin being made authoritative over a regional one.
eventsource = network
eventsourcecode = eid
res, msg = transfer(
config,
doc,
eventsourcecode,
eventsource,
version_folder,
is_scenario=is_scenario,
)
logger.info(msg)
if not res:
logger.critical('Error transferring PAGER content. "%s"' % msg)
print("Created onePAGER pdf %s" % onepager_pdf)
logger.info("Created onePAGER pdf %s" % onepager_pdf)
logger.info("Done.")
return True
except Exception as e:
f = io.StringIO()
traceback.print_exc(file=f)
msg = e
msg = "%s\n %s" % (str(msg), f.getvalue())
hostname = socket.gethostname()
msg = msg + "\n" + "Error occurred on %s\n" % (hostname)
if gridfile is not None:
msg = msg + "\n" + "Error on file: %s\n" % (gridfile)
if eid is not None:
msg = msg + "\n" + "Error on event: %s\n" % (eid)
if pager_version is not None:
msg = msg + "\n" + "Error on version: %i\n" % (pager_version)
f.close()
logger.critical(msg)
logger.info("Sent error to email")
return False