plt.show()
plt.savefig(fp+'plots/modis_only_tau_ref_comp.png',dpi=600)
plt.savefig(fp+'plots/modis_only_tau_ref_comp.pdf',bbox='tight')
# <markdowncell>
# Now load the aircraft telemetry onto the plot
# <codecell>
reload(lm)
# <codecell>
# load the ict file and check out the results
iwg = lm.load_ict(fp+'arm-iop/aaf.iwg1001s.g1.TCAP.20130219.145837.a1.dat')
print iwg.dtype.names
print iwg.dtype.names.index('Date_Time')
print iwg['Date_Time'][0]
print type(iwg['Date_Time'][0])
iwg['Lat']
# <codecell>
iwg_utch = np.array([i.hour+i.minute/60.+i.second/3600.+i.microsecond/3600000. for i in iwg['Date_Time']])
# <codecell>
fig = plt.figure()
fig.add_subplot(3,1,1)
ax = plt.plot(iwg_utch,iwg['Lat'])
cba.ax.set_yticklabels(labels); plt.show() # <headingcell level=2> # Get the 4STAR data # <codecell> import load_modis reload(load_modis) from load_modis import mat2py_time, toutc, load_ict # <codecell> dc8 = load_ict(fp+'dc8/20130913/SEAC4RS-MMS-1HZ_DC8_20130913_RB.ict') # <codecell> # load the matlab file containing the measured TCAP radiances mea = sio.loadmat(fp+'../4STAR/SEAC4RS/20130913/20130913starzen_3.mat') mea.keys() # <markdowncell> # Go through and get the radiances for good points, and for the time selected # <codecell> print mea['t'] tt = mat2py_time(mea['t'])
