def timeseries(nest, loc): # columns are: # col 1: forecast time in hr # col 3,4: nearest grid to stn # col 5: 2m Temp (K) # col 7: U wind # col 8: V # col 9: sfc P (Pa) ts_fname = directory+loc+'.d0'+str(nest)+'.TS' """ txt_fname = directory+loc+'.d0'+str(nest)+'.txt' #pdb.set_trace() try: # print "Looking for .txt time series" testfile = open(txt_fname) except IOError: print "Converting .TS to .txt" os.system('cp ' + ts_fname +' ' + txt_fname) finally: print "Opening .txt time series" ts_hour,ix,iy,t,u,v,psfc = N.loadtxt(txt_fname,'r',usecols=(1,3,4,5,7,8,9),skiprows=1, delimiter='\t') """ ts_hour,ix,iy,t,u,v,psfc = N.loadtxt(ts_fname,usecols=(1,3,4,5,7,8,9),skiprows=1,unpack=True) # Create wind magnitude #wind = N.sqrt(u**2 + v**2) wspd, wdir = generalmet.combine_wind_components(u,v) # Save to pickle for other plots picklepath = '/uufs/chpc.utah.edu/common/home/u0737349/dsws/thesis/timeseries/' savedict = {'wspd':wspd, 'wdir':wdir, 'ts_hour':ts_hour, 'locnum':loc, 'uintah':uintah} picklename = picklepath + loc + uintah + '_WRF.p' pickle.dump(savedict,open(picklename, 'wb')) # Need to create list of times in human format for plot plt.figure(figsize=(width,height)) plt.plot(ts_hour,wspd) plt.plot([42,42],[0,10]) plt.plot([54,54],[0,10]) plt.plot([66,66],[0,10]) #plt.plot(humantime,wind #plt.xticks( #plt.yticks( plt.xlabel('Time') plt.ylabel('Wind speed (m/s)') #plt.title('Meteogram of wind speed with time, WRF output') #plt.show() plt.savefig(outdir+naming+str(nest)+'_'+loc+'_timeseries.png') plt.close()