xlab     = 'Latitude'
ylab     = 'Altitude / km'
clab     = u'\u0394 '+varnames[0]+r' / %'
llim     = -30    # shading limits
ulim     = 30
by       = 5
lclim    = -10    # contour limits
uclim    = 10
cby      = 1
lid      = 20   # y axis limit / km
yby      = 5
cdp      = 0
ylabs    = ["%.0f" % z for z in np.arange(0,lid+yby,yby)]
levs     = np.arange(llim,ulim+by,by)
clevs    = np.arange(lclim,uclim+by,cby)
cols1    = ccol.custom_colors('default')
cols     = ccol.shiftedColorMap(cols1, midpoint=0.5, name='shifted')
#********************************************************************************************************
# Fetch job attributes and files
nrun=len(modnames)
nvar=len(varnames)

# find netcdf files
# in format: [[mod1var1,mod1var2,...],[mod2var1,mod2var2,...],...]
ncmods = []
for i in range(nrun):
    ncmods.append([])
    for j in range(nvar):
      ncpath    = disk+modnames[i]+'_evaluation_output.nc'
      ncmod     = ncdf.Dataset(ncpath,'r')
      ncmods[i].append(ncmod)
var       = jobs2.variable[jobs2.stash.index(stash)]

# range for contour limits 
#levs	= np.arange(1.65,1.95,0.025)

plotname  = jobid+stash+'_'+localtime+'.png'
outdir    = 'xx'
if not os.path.exists(outdir):
    os.makedirs(outdir)

#************************************************************
# label format 
fmtlab    = plots.labels()

# Colours
c=ccol.custom_colors('grads')
cmap = cm.bwr
cnorm=clrs.Normalize(cmap,clip=False)
cmap.set_under(color=cmap(0.0),alpha=1.0)
cmap.set_over(color=cmap(1.0),alpha=1.0)
#************************************************************
# Read in files
# time,model_level_number,latitude,longitude

file1     = '/'+disk+'/ih280/um/'+jobid+'/'+jobid+stash+'.nc'
ncbase    = ncdf.Dataset(file1,'r')

data       = ncbase.variables[var]
print data

# attributes