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):
#read in global config file
configfile = os.path.join(os.path.expanduser('~'),'.lsprocess','lsprocess.cfg')
hasconfig = os.path.isfile(configfile)
if not hasconfig:
print()
print('No config file "%s" found.' % configfile)
print()
sys.exit(1)
global_grids,outfolder = readConfig(configfile) #returns a dictionary just like global_config above
#read in event specific grid file
try:
covdict,predictors,ename = parseEvent(args.eventfile)
except Exception as msg:
print('There is something wrong with your event file. See errors below.')
print(msg)
sys.exit(1)
#construct output folder from global/event configs
outfolder = os.path.join(outfolder,ename)
if not os.path.isdir(outfolder):
os.mkdir(outfolder)
#look for bounding box and resolution in event config file, or get from shakemap
bbox = None
shakemap = ShakeGrid(predictors['shakemap'][0],'MMI')
if 'bbox' in covdict:
bbox = covdict['bbox']
else:
#bbox = shakemap.getRange()
#default to the bounding box of the coverage data
with fiona.open(covdict['filename']) as src:
tbbox = src.bounds
bbox = (tbbox[0],tbbox[2],tbbox[1],tbbox[3])
if 'resolution' in covdict:
resolution = covdict['resolution']
else:
resolution = shakemap.getGeoDict()['xdim']
#get input coverage projection from event config OR from .prj file
#projstr = covdict['projstr']
#get format of coverage, check against list of supported fiona formats, read in data
#we'll do other support later
#if necessary, project coverage into lat/lon
#skip projection for now as well
#determine what the grid shape and (potentially) new bbox is given bbox and resolution
nrows,ncols,bbox = getShape(bbox,resolution)
#if the coverage dataset is larger than the ShakeMap, we need to make sure our output grid
#is contained by the shakemap for interpolation purposes.
shakebounds = shakemap.getRange()
shakexdim,shakeydim = (shakemap.geodict['xdim'],shakemap.geodict['ydim'])
xmin = max(bbox[0],shakebounds[0]+shakexdim*2)
xmax = min(bbox[1],shakebounds[1]-shakexdim*2)
ymin = max(bbox[2],shakebounds[2]+shakeydim*2)
ymax = min(bbox[3],shakebounds[3]-shakeydim*2)
geodict = {'xdim':resolution,'ydim':resolution,
'xmin':xmin,'xmax':xmax,
'ymin':ymin,'ymax':ymax,
'nrows':nrows,'ncols':ncols}
#rasterize projected coverage defined bounding box and resolution
shpfile = covdict['filename']
print('Creating coverage grid...')
covgrid = makeCoverageGrid(shpfile,geodict)
outgridfile = os.path.join(outfolder,'coverage.grd')
print('Saving coverage to %s...' % outgridfile)
covgrid.save(outgridfile)
#make a grid of lat,lon values
row = np.arange(0,nrows)
col = np.arange(0,ncols)
rows = repmat(row,ncols,1).T
cols = repmat(col,nrows,1)
lat,lon = covgrid.getLatLon(rows,cols)
#create a list of arrays that we'll dump out to a text file when done
vardict = {}
vardict['coverage'] = covgrid.griddata.flatten()
vardict['lat'] = lat.flatten()
vardict['lon'] = lon.flatten()
#subset shakemap and global grids using defined bounding box and resolution
shakefile = predictors['shakemap'][0]
variables = predictors['shakemap'][1]
for var in variables:
shakemap = ShakeGrid(shakefile,var.upper())
shakemap.interpolateToGrid(geodict)
gmtshake = GMTGrid()
gmtshake.geodict = shakemap.geodict
gmtshake.griddata = shakemap.griddata
outshakefile = os.path.join(outfolder,'%s.grd' % var)
print('Saving %s to %s...' % (var,outshakefile))
gmtshake.save(outshakefile)
vardict[var] = gmtshake.griddata.flatten()
#write netcdf versions of coverage, shakemap, and global grids to output folder
for gridname,gridfile in global_grids.items():
if not os.path.isfile(gridfile):
pass
try:
grid = sampleGrid(gridfile,geodict)
except Exception as e:
print('There was an error while sampling the "%s" grid "%s". - "%s"' % (gridname,gridfile,str(e)))
outgridfile = os.path.join(outfolder,gridname+'.grd')
print('Saving %s to %s...' % (gridname,outgridfile))
grid.save(outgridfile)
vardict[gridname] = grid.griddata.flatten()
#create text file with columns of data for all predictor variables
firstcols = ['lat','lon','coverage']
outmat = np.zeros((nrows*ncols,len(vardict)))
for i in range(0,len(firstcols)):
col = firstcols[i]
outmat[:,i] = vardict[col]
colidx = i+1
colnames = []
for col,column in vardict.items():
if col in firstcols:
continue
outmat[:,colidx] = vardict[col]
colnames.append(col)
colidx += 1
colnames = firstcols + colnames
m,n = outmat.shape
datfile = os.path.join(outfolder,'%s.dat' % ename)
print('Saving all variables to data file %s...' % datfile)
f = open(datfile,'wt')
f.write(','.join(colnames)+'\n')
for i in range(0,m):
line = ','.join('%.4f' % col for col in outmat[i,:])
f.write(line+'\n')
f.close()
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)
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)
#read in event specific grid file
try:
covdict,predictors,ename = parseEvent(args.eventfile)
except Exception,msg:
print 'There is something wrong with your event file. See errors below.'
print msg
sys.exit(1)
#construct output folder from global/event configs
outfolder = os.path.join(outfolder,ename)
if not os.path.isdir(outfolder):
os.mkdir(outfolder)
#look for bounding box and resolution in event config file, or get from shakemap
bbox = None
shakemap = ShakeGrid(predictors['shakemap'][0],'MMI')
if covdict.has_key('bbox'):
bbox = covdict['bbox']
else:
#bbox = shakemap.getRange()
#default to the bounding box of the coverage data
with fiona.open(covdict['filename']) as src:
tbbox = src.bounds
bbox = (tbbox[0],tbbox[2],tbbox[1],tbbox[3])
if covdict.has_key('resolution'):
resolution = covdict['resolution']
else:
resolution = shakemap.getGeoDict()['xdim']
#get input coverage projection from event config OR from .prj file
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
def getShakeMapParams(self,config,shakefile,geodict):
#get the shakemap params the user wants
smparams = config.get('SHAKEMAP','variables').split(',')
#load the shakemap
intset = set(SM_TERMS).intersection(smparams)
if not len(intset):
print 'The allowed ShakeMap variables are: "%s". Your config file has "%s".' % (str(SM_TERMS),str(smparams))
sys.exit(1)
shakedict = {}
shakemap = None
if 'PGA' in smparams:
shakemap = ShakeGrid(shakefile,variable='PGA')
shakemap.interpolateToGrid(geodict)
tmpgrid = gmt.GMTGrid()
tmpgrid.loadFromGrid(shakemap)
shakedict['PGA'] = tmpgrid
if 'PGV' in smparams:
shakemap = ShakeGrid(shakefile,variable='PGV')
shakemap.interpolateToGrid(geodict)
tmpgrid = gmt.GMTGrid()
tmpgrid.loadFromGrid(shakemap)
shakedict['PGV'] = tmpgrid
if 'MMI' in smparams:
shakemap = ShakeGrid(shakefile,variable='MMI')
shakemap.interpolateToGrid(geodict)
tmpgrid = gmt.GMTGrid()
tmpgrid.loadFromGrid(shakemap)
shakedict['MMI'] = tmpgrid
if 'MW' in smparams:
if shakemap is None:
shakemap = ShakeGrid(shakefile,variable='MMI')
attdict = shakemap.getAttributes()
shakedict['MW'] = attdict['event']['magnitude']
return (shakedict)
def main(args):
#define location for config file
homedir = os.path.expanduser("~") #where is the user's home directory?
configfile = args.configFile
shakefile = args.shakefile
if not os.path.isfile(shakefile):
if isURL(shakefile):
shakefile = getGridURL(shakefile) #returns a file object
else:
print 'Could not find "%s" as a file or a url. Returning.' % (shakefile)
shakemap = ShakeGrid(shakefile)
#figure out the bounds that are greater than the biggest bounds
#of any of the grids
shakerange = shakemap.getRange()
lonrange = shakerange[1] - shakerange[0]
latrange = shakerange[3] - shakerange[2]
xmin = shakerange[0] - lonrange*0.1
xmax = shakerange[1] + lonrange*0.1
ymin = shakerange[2] - latrange*0.1
ymax = shakerange[3] + latrange*0.1
bigbounds = (xmin,xmax,ymin,ymax)
#
shakeheader = shakemap.getAttributes()
edict = {'mag':shakeheader['event']['magnitude'],
'time':shakeheader['event']['event_timestamp'],
'loc':shakeheader['event']['event_description'],
'epicenter':(shakeheader['event']['lat'],shakeheader['event']['lon']),
'version':int(shakeheader['shakemap_grid']['shakemap_version']),
'eventid':shakeheader['shakemap_grid']['event_id']}
config = ConfigParser.RawConfigParser()
config.read(configfile)
network = shakeheader['shakemap_grid']['shakemap_originator']
eventcode = shakeheader['shakemap_grid']['shakemap_id']
if eventcode.startswith(network):
eventid = eventcode
else:
eventid = network + eventcode
outfolder = os.path.join(config.get('OUTPUT','folder'),eventid)
if not os.path.isdir(outfolder):
os.makedirs(outfolder)
slopefile = config.get('MAPDATA','slope')
slopegrid = GMTGrid(slopefile,bounds=shakemap.getRange())
slopeout = os.path.join(outfolder,'slope.grd')
cityfile = config.get('MAPDATA','cityfile')
#get all of the colors that people want
colors = {}
for option in config.options('MAPDATA'):
if option.endswith('color'):
colors[option] = config.get('MAPDATA',option)
#if they have roads configured, go find the appropriate roads segments
hasRoads = config.has_option('MAPDATA','roadfolder')
roadslist = []
if hasRoads and args.roads:
roadroot = config.get('MAPDATA','roadfolder')
xmin,xmax,ymin,ymax = shakemap.getRange()
for folder in os.listdir(roadroot):
roadfolder = os.path.join(roadroot,folder)
shpfiles = glob.glob(os.path.join(roadfolder,'*.shp'))
if len(shpfiles):
shpfile = shpfiles[0]
f = fiona.open(shpfile)
shapes = list(f.items(bbox=(xmin,ymin,xmax,ymax)))
for shapeid,shapedict in shapes:
roadslist.append(shapedict)
f.close()
#get the thresholds for liquefaction/landslide model
slopemin = float(config.get('MAPDATA','slopemin'))*100
slopemax = float(config.get('MAPDATA','slopemax'))*100
probdict = {}
gridbounds = [999,-999,999,-999] #this will hold the smallest bounding box enclosing both models
for model in getModelNames(configfile):
lm = LogisticModel(configfile,shakefile,model)
colormaps = getColorMaps(configfile)
print 'Equation for %s model:' % model
print
print lm.getEquation()
print
P = lm.calculate()
probgrid = GMTGrid()
probgrid.griddata = P.copy()
probgrid.geodict = lm.layerdict[lm.layerdict.keys()[0]].geodict.copy()
#resample the slope grid to model
slopegrid2 = GMTGrid()
slopegrid2.loadFromGrid(slopegrid)
slopegrid2.interpolateToGrid(probgrid.geodict)
if model == 'liquefaction':
ithresh = slopegrid2.griddata > slopemax
else:
ithresh = slopegrid2.griddata < slopemin
probgrid.griddata[ithresh] = 0.0
xmin,xmax,ymin,ymax = probgrid.getRange()
if xmin < gridbounds[0]:
gridbounds[0] = xmin
if xmax > gridbounds[1]:
gridbounds[1] = xmax
if ymin < gridbounds[2]:
gridbounds[2] = ymin
if ymax > gridbounds[3]:
gridbounds[3] = ymax
probdict[model] = probgrid
probfile = os.path.join(outfolder,'%s.grd' % model)
print 'Saving %s model output to %s' % (model,probfile)
probgrid.save(probfile)
#renderPanel(lm,colormaps,outfolder,edict)
# for layername,layergrid in lm.layerdict.iteritems():
# layerfile = os.path.join(outfolder,layername+'.grd')
# print 'Saving input grid %s to %s...' % (layername,layerfile)
# layergrid.save(layerfile)
# renderLayer(layergrid,layername,outfolder,edict,model,colormaps)
topofile = config.get('MAPDATA','topo')
#bigbounds = shakemap.getRange()
xdim = shakemap.geodict['xdim']
ydim = shakemap.geodict['xdim']
#bigbounds = (bigbounds[0]-xdim*4,bigbounds[1]+xdim*4,bigbounds[2]-ydim*4,bigbounds[3]+ydim*4)
topogrid = GMTGrid(topofile,bounds=bigbounds)
topogrid = adjustTopoGrid(topogrid,bigbounds) #make this grid as big as bigbounds if we hit an upper or lower bound
topoout = os.path.join(outfolder,'topography.grd')
print 'Saving topography to %s' % topoout
topogrid.save(topoout)
print 'Saving slope to %s' % slopeout
slopegrid.save(slopeout)
isScenario = shakeheader['shakemap_grid']['shakemap_event_type'].lower() == 'scenario'
if args.noscenario:
isScenario = False
timestr = renderDate(shakeheader['event']['event_timestamp'])
location = shakeheader['event']['event_description']
#hillshfile = config.get('MAPDATA','hillshadefile')
#hillshgrid = GMTGrid(hillshfile,bounds=bigbounds)
makeDualMap(probdict['liquefaction'],probdict['landslide'],topogrid,slopegrid,edict,outfolder,isScenario=isScenario,roadslist=roadslist,colors=colors,cityfile=cityfile)
