def main(args, config):
eventid = args.eventID
shakehome = config.get('SHAKEMAP', 'shakehome')
xmlfile = os.path.join(shakehome, 'data', eventid, 'input', args.dataFile)
gridfile = os.path.join(shakehome, 'data', eventid, 'output', 'grid.xml')
#list of grid.xml variable names and corresponding data file variable names
variables = [('PGA', 'acc'), ('PGV', 'vel'), ('PSA03', 'psa03'),
('PSA10', 'psa10'), ('PSA30', 'psa30')]
shakemap = ShakeGrid(gridfile, variable='MMI') #doesn't matter
gdict = shakemap.getGeoDict()
atts = shakemap.getAttributes()
location = atts['event']['event_description']
etime = atts['event']['event_timestamp']
epilat = atts['event']['lat']
epilon = atts['event']['lon']
nrows = gdict['nrows']
ncols = gdict['ncols']
root = minidom.parse(xmlfile)
f = plt.figure(figsize=(8.5, 11))
pnum = 1
pgaobs = []
pgaexp = []
pgadist = []
for vartuple in variables:
gridvar, stationvar = vartuple
shakemap = ShakeGrid(gridfile, variable=gridvar)
stations = root.getElementsByTagName('station')
observed = []
expected = []
for i in range(0, len(stations)):
station = stations[i]
lat = float(station.getAttribute('lat'))
lon = float(station.getAttribute('lon'))
row, col = shakemap.getRowCol(lat, lon)
if row < 0 or row > nrows or col < 0 or col > ncols:
continue
pgael = station.getElementsByTagName(
'comp')[0].getElementsByTagName(stationvar)[0]
pga = float(pgael.getAttribute('value'))
gridpga = shakemap.getValue(lat, lon)
observed.append(pga)
expected.append(gridpga)
if gridvar == 'PGA':
pgaobs.append(pga)
pgaexp.append(gridpga)
distance, az1, az2 = gps2DistAzimuth(epilat, epilon, lat, lon)
pgadist.append(distance / 1000.0)
observed = np.array(observed)
expected = np.array(expected)
xmax = observed.max()
ymax = expected.max()
dmax = max(xmax, ymax) * 1.05
v = [0, dmax, 0, dmax]
plt.subplot(3, 2, pnum)
plt.plot(observed, expected, 'b.')
plt.xlabel('Observed %s' % gridvar)
plt.ylabel('Modeled %s' % gridvar)
plt.axis(v)
pnum += 1
#Add in one final plot - pga differences vs distance, just to see if that's a factor
pgaobs = np.array(pgaobs)
pgaexp = np.array(pgaexp)
pgadist = np.array(pgadist)
pgadiff = np.power((pgaobs - pgaexp), 2)
mdiff = np.mean(pgadiff)
stddiff = np.std(pgadiff)
ymax = mdiff + 2 * stddiff
plt.subplot(3, 2, 6)
plt.plot(pgadist, pgadiff, 'b.')
plt.ylabel('pga diff (squared)')
plt.xlabel('Distance (km)')
plt.axis([0, pgadist.max(), 0, ymax])
f.suptitle('Event %s %s - %s' %
(eventid, etime.strftime('%Y-%m-%d %H:%M:%S'), location))
plt.savefig('%s_qa.pdf' % eventid)
def main(args):
globaldict = getGlobalConfig()
shakehome = globaldict['shakehome']
popfile = globaldict['popfile']
if shakehome is None:
print 'Cannot find ShakeMap home folder on this system.'
sys.exit(1)
datadir = os.path.join(shakehome,'data',args.event)
if not os.path.isdir(datadir):
print 'Cannot find event %s on the system' % args.event
sys.exit(1)
#Make sure the timeoutput folder is there (can't put our time grids in output - that gets
#wiped out every time shakemap runs
outfolder = os.path.join(datadir,'timeoutput')
if not os.path.isdir(outfolder):
os.makedirs(outfolder)
#now look for config file in top-level folder
configfile = os.path.join(datadir,'alert.conf')
if not os.path.isfile(configfile):
print 'Cannot find alert config file for %s in the data directory' % args.event
sys.exit(1)
config = ConfigParser.ConfigParser()
config.readfp(open(configfile))
#get the bounds of the map so we can find cities
xmin = float(config.get('MAP','xmin'))
xmax = float(config.get('MAP','xmax'))
ymin = float(config.get('MAP','ymin'))
ymax = float(config.get('MAP','ymax'))
citylist = getCityList(xmin,xmax,ymin,ymax,globaldict['cityfile'])
#Get the MMI threshold below which alert times will NOT be saved
mmithresh = float(config.get('MAP','mmithresh'))
#get the array of epicenters
lats = [float(p) for p in config.get('FAULT','lats').split()]
lons = [float(p) for p in config.get('FAULT','lons').split()]
#write out a new grind.conf file
writeGrind(config,datadir)
#instantiate our p/s travel time calculator
calc = TravelTimeCalculator()
#where is the grind binary?
grindbin = os.path.join(shakehome,'bin','grind')
#specify the event.xml file, get the depth of the event
eventfile = os.path.join(datadir,'input','event.xml')
root = parse(eventfile)
eq = root.getElementsByTagName('earthquake')[0]
depth = float(eq.getAttribute('depth'))
root.unlink()
#get the dimensionality of the grid file and of the pop grid we'll interpolate to
gridfile = os.path.join(datadir,'output','grid.xml')
if not os.path.isfile(gridfile):
grindcmd = '%s -event %s' % (grindbin,args.event)
res,stdout,stderr = getCommandOutput(grindcmd)
mmigrid = ShakeGrid(gridfile,variable='MMI')
popgrid = EsriGrid(popfile)
popgrid.load(bounds=mmigrid.getRange())
m,n = popgrid.griddata.shape
#loop over all the event realizations
timefiles = []
timestack = np.zeros((m,n,len(lats)),dtype=np.float32)
for i in range(0,len(lats)):
print 'Calculating arrival times for scenario %i of %i' % (i+1,len(lats))
lat = lats[i]
lon = lons[i]
if i == 0:
lonoff = 0
latoff = 0
else:
lonoff = -1* (lons[i] - lons[i-1])
latoff = lats[i] - lats[i-1]
#modify the event.xml file to have the new lat/lon epicenter
sourcetext = getEventText(eventfile,lat,lon)
f = open(eventfile,'wt')
f.write(sourcetext)
f.close()
sdict = getSlowestStation(lat,lon,depth,calc)
ptime = sdict['time']
stationlat = sdict['lat']
stationlon = sdict['lon']
grindcmd = '%s -latoff %f -lonoff %f -event %s' % (grindbin,latoff,lonoff,args.event)
res,stdout,stderr = getCommandOutput(grindcmd)
if not res:
print 'Grind command failed: "%s", "%s"' % (stdout,stderr)
sys.exit(1)
#Get the grid.xml output, do some time calculations
mmigrid = ShakeGrid(gridfile,variable='MMI')
timegrid = np.zeros((m,n),dtype=np.float32)
for row in range(0,m):
for col in range(0,n):
mmilat,mmilon = mmigrid.getLatLon(row,col)
distance = locations2degrees(lat,lon,mmilat,mmilon)
tmp,stime = calc.getTravelTimes(distance,depth)
timegrid[row,col] = stime - ptime
#debugging
f = plt.figure()
plt.subplot(2,1,1)
plt.imshow(mmigrid.griddata)
plt.colorbar()
plt.subplot(2,1,2)
plt.imshow(timegrid)
plt.colorbar()
plt.savefig(os.path.join(outfolder,'timegrid.png'))
plt.close(f)
with warnings.catch_warnings():
warnings.simplefilter("ignore")
exposure,timegrid = getTimeExposure(timegrid,mmigrid,popfile,mmithresh)
print 'Population Warning Times for epicenter %.4f,%.4f' % (lat,lon)
printExposure(exposure)
expofile = os.path.join(outfolder,'expo%03i.json' % (i+1))
f = open(expofile,'wt')
f.write(json.dumps(exposure))
f.close()
timefile = os.path.join(outfolder,'timegrid%03i.flt' % (i+1))
timefiles.append(timefile)
metadict = {'epilat':lat,'epilon':lon,'eventid':args.event}
saveTimeGrid(timefile,timegrid,mmigrid.geodict,metadict)
timestack[:,:,i] = timegrid
alertgrid = popgrid
alertgrid.griddata = timegrid
makeMap(alertgrid,'alertmap_%i' % i,outfolder,popfile,globaldict['popcolormap'],sdict,citylist,[lat],[lon])
methods = config.get('MAP','output').split(',')
for method in methods:
if method == 'median':
statgrid = np.median(timestack,axis=2)
if method == 'mean':
statgrid = np.nanmean(timestack,axis=2)
if method == 'min':
statgrid = np.nanmin(timestack,axis=2)
if method == 'max':
statgrid = np.nanmax(timestack,axis=2)
timegrid = popgrid
timegrid.griddata = statgrid
makeMap(timegrid,method,outfolder,popfile,globaldict['popcolormap'],sdict,citylist,lats,lons)
from Correlation.loop import main
from Correlation.realizations import realizations
from Correlation.plotting import plot
voi = 'PGA'
r = [45]
num_realizations = 100
corr_model = 'JB2009'
vscorr = True
plot_on = False
for R in range(0, np.size(r)):
radius = r[R]
# Get shakemap for desired variable, PGA, uncertainty grid and stationdata
shakemap = ShakeGrid('Inputs/grid.xml', variable='%s' % voi)
# Uncertainty Data: Units in ln(pctg)
unc_INTRA = ShakeGrid('Inputs/uncertainty.xml',
variable='GMPE_INTRA_STD%s' % voi)
unc_INTER = ShakeGrid('Inputs/uncertainty.xml',
variable='GMPE_INTER_STD%s' % voi)
# Station Data: Units in pctg
stationlist = 'Inputs/stationlist.xml'
stationdata = readStation(stationlist)
print 'Calling initialize'
variables = initialize(shakemap, unc_INTRA, unc_INTRA, stationdata)
print 'Radius: ', radius
