def diff1(king,king_dat,output,high=True,type='thpv2',v='v',monte=False,sttest=True,tcrit=0.87,graph=True,filled=False,sig=False,monthly=1,trials=1000,cutoff=0.90):
#################################################################
# METHOD: 25/11/13 #
# #
# take high/low solar data #
# compute average blocking frequency for each lat lon point #
# then difference from all-time data (climatological data) #
# plot this difference using basemap and compare to Woolings #
# Note: this function returns the difference data #
# #
#################################################################
try:
from open import open_pkl
#read in x-y data
opt = []
data_xy = open_pkl(king_dat,'era40.gga'+v+'.year-2002.month-01.b.'+type+'_003.duration_ge_5_day.pkl')
Lon,Lat = data_xy['lon']['lon'],data_xy['lat']['lat']
Lon = np.append(Lon,360+Lon[0])
#print Lon
X,Y = meshgrid(Lon,Lat)
opt.append(X)
opt.append(Y)
# #read in data
if high == True:
data = read_list(king+'high_era40_blocking_'+type+'.list',king_dat)
#generate listname
listnm = 'era40_blocking_'+str(type)+'_high_blk'
stype = 'high'
elif high != True:
data = read_list(king+'low_era40_blocking_'+type+'.list',king_dat)
#generate listname
listnm = 'era40_blocking_'+str(type)+'_low_blk'
stype = 'low'
clim = read_list(king+'era40_blocking_'+type+'.list',king_dat)
#checks of data read in
if len(data) != len(clim) or len(data[0]) != len(clim[0]):
print "Error: Array lengths don't match\nData: "+str(len(data)),str(len(data[0]))+"\nClim: "+str(len(clim)),str(len(clim[0]))
return 0
#compute difference array
diff = zeros(shape=(len(data),len(data[0])+1))
test = []
for lat in range(0,len(data)):
for lon in range(0,len(data[0])):
diff[lat][lon] = -clim[lat][lon] + data[lat][lon]
#final value for diff
for lat in range(0, len(data)):
diff[lat][-1] = -clim[lat][0] + data[lat][0]
opt.append(diff)
if sig == True:
try:
from sig_test import sig_test
regions = sig_test(list_name='era40_blocking_thpv2.list',list_dir=king,monte=monte,sttest=sttest,tcrit=tcrit,data_dir=king_dat,high=high,trials=1000,cutoff=cutoff)
extra = regions[:,0]
extra.shape = (regions[:,0].shape[0],1)
regions = np.concatenate((regions,extra),1)
except ValueError as err: print "Value Error: " + str(err)
if graph == True:
#generate output filename
if monte == True: sgtype = 'monte'
if sttest == True: sgtype = 'ttest'
output = str(output)+'blk'+str(listnm)+str(sgtype)+str(int(100*(1-cutoff)+1))+'.png'
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
# use low resolution coastlines.
fig,ax = plt.subplots()
# fig = plt.figure()
map = fig.add_subplot()
map = Basemap(boundinglat=Lat[-1],lon_0=0,projection='npaeqd',resolution='l',round=True)
lon,lat = np.array(opt[0]),np.array(opt[1])
x,y = map(lon,lat)
# draw coastlines, country boundaries, fill continents.
map.drawcoastlines(linewidth=0.25)
map.drawcountries(linewidth=0.25)
# draw the edge of the map projection region (the projection limb)
map.drawmapboundary()
#if sig == True: map.fill()
if filled == False:
a = np.array(range(-100,102,2))/float(100)
p = map.contour(x,y,np.array(opt[2]),a,colors='k')
elif filled == True:
a = np.array(range(-100,102,2))/float(100)
c = map.contour(x,y,np.array(opt[2]),10,linestyles='solid',colors='black')
p = map.contourf(x,y,-np.array(opt[2]),10,cmap=cm.RdBu,vmin=np.array(opt[2]).min(),vmax=np.array(opt[2]).max(),alpha=0.5,)
cb = fig.colorbar(p, ax=ax)
t = ax.set_title('blk'+stype+'-clim')
if sig == True:
# masking the array
regions = np.ma.array(regions)
interior = regions < 0.5
regions[interior] = np.ma.masked
s = map.contourf(x,y,regions,1,cmap=cm.gray_r)
t = ax.set_title('blk'+str(stype)+'-clim (sig '+str(int(100*(1.0-cutoff)+1))+'%)')
fig.savefig(str(output))
return opt
except IOError as err:
print "File error: " + str(err)
except ValueError as err:
print "Value Error: " + str(err)
return 0 #compute difference array diff = zeros(shape=(len(data),len(data[0])+1)) test = [] for lat in range(0,len(data)): for lon in range(0,len(data[0])): diff[lat][lon] = -clim[lat][lon] + data[lat][lon] #final value for diff for lat in range(0, len(data)): diff[lat][-1] = -clim[lat][0] + data[lat][0] opt.append(diff) if sig == True: try: from sig_test import sig_test regions = sig_test(list_name='era40_blocking_thpv2.list',list_dir=king,monte=monte,sttest=sttest,tcrit=tcrit,data_dir=king_dat,high=high,trials=1000,cutoff=cutoff) extra = regions[:,0] extra.shape = (regions[:,0].shape[0],1) regions = np.concatenate((regions,extra),1) except ValueError as err: print "Value Error: " + str(err) if graph == True: #generate output filename if monte == True: sgtype = 'monte' if sttest == True: sgtype = 'ttest' output = str(output)+'blk'+str(listnm)+str(sgtype)+str(int(100*(1-cutoff)+1))+'.png' from mpl_toolkits.basemap import Basemap import matplotlib.pyplot as plt # use low resolution coastlines.
