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):
#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()
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.iteritems():
if not os.path.isfile(gridfile):
pass
try:
grid = sampleGrid(gridfile,geodict)
except Exception,e: