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()