def readTimeGrid(timefile): stkeys = ['TOTALROWBYTES','NBITS','LAYOUT','YDIM','NCOLS', 'BANDROWBYTES','PIXELTYPE','XDIM','NROWS', 'NBANDS','ULXMAP','ULYMAP','BYTEORDER'] src = rasterio.open(timefile,'r',driver='EHdr') timedata, = src.read() m,n = timedata.shape aff = src.affine xdim = aff[0] xmin = aff[2] ydim = -aff[4] ymax = aff[5] src.close() timegrid = GMTGrid() timegrid.griddata = timedata timegrid.geodict = {'nrows':m,'ncols':n,'nbands':1,'bandnames':['Alert Time'], 'xmin':xmin,'xmax':xmin+n*xdim,'ymin':ymax-m*ydim,'ymax':ymax, 'xdim':xdim,'ydim':ydim} timepath,timefile = os.path.split(timefile) timebase,timext = os.path.splitext(timefile) timehdr = os.path.join(timepath,timebase+'.hdr') timedict = readTimeHeader(timehdr) for key in stkeys: timedict.pop(key) for key,value in timedict.iteritems(): if isinstance(value,str): timedict[key] = value.replace('"','') return (timegrid,timedict)
def renderPanel(logmodel, colormaps, outfolder, edict): nparray = "<type 'numpy.ndarray'>" # first, figure out how many layers we have layerdict = logmodel.layerdict outfiles = [] for smterm in model.SM_TERMS: for term in logmodel.terms.values(): if term.find(smterm) > -1 and not isinstance(logmodel.shakedict[smterm], float): layerdict[smterm] = logmodel.shakedict[smterm] for layername, layergrid in layerdict.iteritems(): fig = plt.figure(figsize=(8, 8)) ax = plt.gca() renderLayer(layername, layergrid, outfolder, edict, fig, ax, logmodel.model, colormaps) outfile = os.path.join(outfolder, "%s_%s.pdf" % (layername, logmodel.model)) print "Saving input layer %s to %s" % (layername, outfile) plt.savefig(outfile) outfiles.append(outfile) outfile = os.path.join(outfolder, "%s_model.pdf" % logmodel.model) fig = plt.figure(figsize=(8, 8)) ax = plt.gca() P = logmodel.calculate() pgrid = GMTGrid() pgrid.griddata = P.copy() pgrid.geodict = layergrid.geodict.copy() renderLayer(logmodel.model, pgrid, outfolder, edict, fig, ax, logmodel.model, colormaps) print "Saving %s model to %s" % (logmodel.model, outfile) outfiles.append(outfile) return outfiles
def makeCoverageGrid(covshp,geodict): shapes = fiona.open(covshp) geoms = [] for shape in shapes: geoms.append(shape['geometry']) shapes.close() outshape = (geodict['nrows'],geodict['ncols']) transform = Affine.from_gdal(geodict['xmin'],geodict['xdim'],0.0,geodict['ymax'],0.0,-geodict['ydim']) img = features.rasterize(geoms,out_shape=outshape,fill=0, transform=transform,all_touched=True, default_value=1) covgrid = GMTGrid() covgrid.geodict = geodict covgrid.griddata = np.int8(img.copy()) return covgrid
def getTimeExposure(timegriddata,mmigrid,popfile,mmithresh): timegrid = GMTGrid() timegrid.griddata = timegriddata.copy() timegrid.geodict = mmigrid.geodict.copy() popgrid = EsriGrid(popfile) popgrid.load(bounds=timegrid.getRange()) timegrid.interpolateToGrid(popgrid.geodict) timegrid.griddata[mmigrid.griddata < mmithresh] = np.NaN times = np.arange(MINTIME,MAXTIME+DTIME,DTIME) exposure = [] mintime = MINTIME ireal = np.isfinite(timegrid.griddata) for time in times[1:]: ipop = ((timegrid.griddata >= mintime) & (timegrid.griddata < time) & np.isfinite(timegrid.griddata)) exposum = int(np.sum(popgrid.griddata[ipop])) exposure.append({'mintime':mintime,'maxtime':time,'exposure':exposum}) mintime = time return (exposure,timegrid.griddata)
def readTimeGrid(timefile): stkeys = [ 'TOTALROWBYTES', 'NBITS', 'LAYOUT', 'YDIM', 'NCOLS', 'BANDROWBYTES', 'PIXELTYPE', 'XDIM', 'NROWS', 'NBANDS', 'ULXMAP', 'ULYMAP', 'BYTEORDER' ] src = rasterio.open(timefile, 'r', driver='EHdr') timedata, = src.read() m, n = timedata.shape aff = src.affine xdim = aff[0] xmin = aff[2] ydim = -aff[4] ymax = aff[5] src.close() timegrid = GMTGrid() timegrid.griddata = timedata timegrid.geodict = { 'nrows': m, 'ncols': n, 'nbands': 1, 'bandnames': ['Alert Time'], 'xmin': xmin, 'xmax': xmin + n * xdim, 'ymin': ymax - m * ydim, 'ymax': ymax, 'xdim': xdim, 'ydim': ydim } timepath, timefile = os.path.split(timefile) timebase, timext = os.path.splitext(timefile) timehdr = os.path.join(timepath, timebase + '.hdr') timedict = readTimeHeader(timehdr) for key in stkeys: timedict.pop(key) for key, value in timedict.iteritems(): if isinstance(value, str): timedict[key] = value.replace('"', '') return (timegrid, timedict)
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()
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: print 'There was an error while sampling the "%s" grid "%s". - "%s"' % (gridname,gridfile,str(e))
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)