Estuary+Python
Python codes for data analysis
2015/10/22 Time series
(c) 2014-12-04 Teruhisa Okada
import netCDF4 import matplotlib.pyplot as plt riverfile = '/Users/teruhisa/mpi00/fujii/Data/osaka-bay_river_201206-2_LQ2.nc' river = netCDF4.Dataset(riverfile, 'r') time = nc.variables['river_time'][:] q = nc.variables['river_transport'][:,:] yodo = q[:,6] yamato = q[:,11] rainfile = '/Users/teruhisa/mpi00/fujii/Data/osaka-bay_rain_201208.nc' r = netCDF4.Dataset(rainfile,'r') rtime = r.variables['rain_time'][:] rain = r.variables['rain'][:,0,0] fig, ax = plt.subplots(1,1,figsize=[10,2]) ax2 = ax.twinx() ax.plot(time-60, -yodo*2, 'k-', label='Yodo R.') ax.plot(time-60, -yamato*2, 'k--', label='Yamato R.') ax.set_xlim(23,25) ax.set_ylim(0,300) ax.set_xticklabels(['23 0:00','23 12:00','24 0:00','24 12:00','25 0:00']) ax.set_xlabel('August, 2012') ax.set_ylabel("River discharge [m s$^{-1}$]") ax.grid() ax.legend(loc=2) ax2.bar(rtime-61, -rain, align='center', width=0.03, alpha=0.7, label='Osaka') ax2.set_ylim(-0.006, 0) ax2.set_ylabel('Rain fall rate [kg m$^{2}$ s$^{-1}$]') ax2.legend(loc=1) plt.savefig('check_river_rain.png', bbox_inches='tight') #plt.show(fig)
Teruhisa Okada
