# <codecell>
import run_kisq_retrieval as rk
reload(rk)
# <codecell>
print max(meas.good)
print type(mea['good'])
print isinstance(mea['good'],tuple)
print type(mea['good'][0])
# <codecell>
(meas.tau,meas.ref,meas.phase,meas.ki) = rk.run_retrieval(meas,lut)
# <codecell>
print meas.utc.shape
print len(meas.good), max(meas.good)
# <codecell>
from Sp_parameters import smooth
fig,ax = plt.subplots(4,sharex=True)
ax[0].set_title('Retrieval results time trace')
ax[0].plot(meas.utc,meas.tau,'rx')
ax[0].plot(meas.utc[meas.good],smooth(meas.tau[meas.good],20),'k')
ax[0].set_ylabel('$\\tau$')
ax[1].plot(meas.utc,meas.ref,'g+')
# <codecell> import run_kisq_retrieval as rk reload(rk) import Sp_parameters as Sp reload(Sp) #del lut #del meas # <codecell> print max(meas.good) # <codecell> (tau,ref,phase,ki) = rk.run_retrieval(meas,lut) # <codecell> del lut # <codecell> print meas.utc.shape print len(meas.good), max(meas.good) # <codecell> reload(Sp) from Sp_parameters import smooth
#i999,i992 = np.argmin(abs(meas.wvl-999)),np.argmin(abs(meas.wvl-992))
i981,i982 = 1039,1040
#ss = np.nanstd(meas.norm[meas.good,i980:i995],axis=1)/np.nanmean(meas.norm[meas.good,i980:i995],axis=1)
sss = abs(meas.norm[meas.good,i981]-meas.norm[meas.good,i982])
#flt = (meas.norm[meas.good,i500]>0.4) & (ss<0.05)
flt = sss<0.1 #(meas.norm[meas.good,i500]>0.4) & (sss<0.1)
#import pdb; pdb.set_trace()
meas.good = meas.good[flt]
if debug:
try:
print lut[i].__dict__.keys()
except Exception as ei:
print 'exception: {}'.format(ei)
import pdb; pdb.set_trace()
print 'meas.good lengh: {},meas.utc length: {}'.format(meas.good.shape,meas.utc.shape)
tau,ref,phase,ki = rk.run_retrieval(meas,lut[i],force_liq=forceliq,force_ice=forceice)
meas.taut[meas.good] = tau[meas.good]
meas.ref[meas.good] = ref[meas.good]
meas.phase[meas.good] = phase[meas.good]
meas.ki[meas.good] = ki[meas.good]
# In[ ]:
meas.tau = meas.taut
# ## Save the retrieval results
# In[ ]: