def corrCalc(his, fut, wavenumber, lev, lons):
"""
Calculate correlations for each ensemble member to understand the spread
in linear interference for each wave during the set month
"""
if wavenumber == 'all':
hisw = his[0]
futw = fut[0]
lon = lons[0]
elif wavenumber == '1':
hisw = his[1]
futw = fut[1]
lon = lons[1]
elif wavenumber == '2':
hisw = his[2]
futw = fut[2]
lon = lons[2]
else:
print(ValueError('WRONG WAVE NUMBER!'))
corrs = np.empty((futw.shape[0]))
for i in range(futw.shape[0]):
corrs[i] = UT.calc_spatialCorrHeight(hisw, futw[i], lev, lon[i], 'yes')
return corrs
###########################################################################
###########################################################################
#### Plot climatological waves
plt.rc('text',usetex=True)
plt.rc('font',**{'family':'sans-serif','sans-serif':['Avant Garde']})
### Set limits for contours and colorbars
zscale = np.array([1000,700,500,300,200,
100,50,30,10])
fig = plt.figure()
for i in range(3):
ax1 = plt.subplot(3,1,i+1)
### Calculate correlations
corr = UT.calc_spatialCorrHeight(historicalforced[i],futureforced[i],
lev,lonss[i],'yes')
lonq,levq = np.meshgrid(lonss[i],lev)
ax1.spines['top'].set_color('dimgrey')
ax1.spines['right'].set_color('dimgrey')
ax1.spines['bottom'].set_color('dimgrey')
ax1.spines['left'].set_color('dimgrey')
ax1.spines['left'].set_linewidth(2)
ax1.spines['bottom'].set_linewidth(2)
ax1.spines['right'].set_linewidth(2)
ax1.spines['top'].set_linewidth(2)
ax1.tick_params(axis='y',direction='out',which='major',pad=3,
width=2,color='dimgrey')
ax1.tick_params(axis='x',direction='out',which='major',pad=3,
width=2,color='dimgrey')