def monthly_to_annual(field, lats, lons, tims, axix_no):
area = gbox_areas(len(lats), len(lons))
# Do weighting
field_av = np.zeros(len(tims))
for i in range(len(tims)):
field_av[i] = np.average(field[i, :, :], weights=area)
nyrs = len(tims) / 12
print nyrs
yrs = np.arange(nyrs)
field_ann = np.zeros([nyrs])
for i in range(0, nyrs):
field_ann[i] = np.average(field_av[12 * i:12 * i + 12])
return field_ann
#var_2='field614' #COA
var2='field643'
#
varn='samalas_sulfate_glob'
print var
# Plotting Arguments
#levs=[50,100,150,200,250,300,350,400,450,500]
colmap='Spectral'
#cbar_label='Ozone Column / DU'
levs=[0.1,0.2,0.5,1.0,2.0,5.0]
cmap=plt.cm.get_cmap(colmap)
levs2=np.insert(levs,0,levs[0]-1)
levs2=np.append(levs2,levs2[len(levs2)-1]+1)
norm=mpl.colors.BoundaryNorm(levs2, ncolors=cmap.N, clip=True)
#levs=[0,60,120,180,240,300,360,420]
areas=gbox_areas(73,96)
outdir='/home/users/dcw32/figures/thesis_volcano/samalas/'
outname=varn+'_surftimese_plot'+time.strftime("%Y%m%d")
save=True
format='png'
extend='both'
mm1=24
mm2=24
mm3=24
mm4=24
#mm=240
####################################################################
#
# Extract
fig=plt.figure()
gs1 = gridspec.GridSpec(1, 1)
#Gridbox weights
lon_maxs=lons+dlon/2.
lon_mins=lons-dlon/2.
enso_w=np.zeros([len(lats),len(lons)])
for i in range(len(lons)):
if lon_maxs[i]<lon_maxi:
if lon_mins[i]>lon_mini:
#5N-5S
enso_w[34:38,i]=1.0
elif lon_maxs[i]>lon_mini:
enso_w[34:38,i]=(lon_maxs[i]-lon_mini)/dlon
elif lon_mins[i]<lon_maxi:
if lon_mins[i]>lon_mini:
enso_w[34:38,i]=(lon_maxi-lon_mins[i])/dlon
#Now
area=gbox_areas(len(lats),len(lons))
area=area*enso_w
enso=np.zeros([len(time)])
enso_ra=np.zeros([len(time)])
for k in range(len(time)):
enso[k]=np.average(sst[k,:,:],weights=area)
for k in range(len(time)):
if k>1:
enso_ra[k]=np.mean(enso[k-2:k+1])
elif k>0:
enso_ra[k]=np.mean(enso[k-1:k+1])
else:
enso_ra[k]=enso[k]
for mons in range(12):
gm_mon=np.mean(enso_ra[mons::12])
enso_ra[mons::12]=enso_ra[mons::12]-gm_mon
