else:
if future:
ys = '2065_2099'
else:
ys = moddct['yrfname']
### Location for olr input & outputs
olrfile = bkdir + dset + '/'+name+'/' + name + '.' + globv + \
'.mon.mean.' + ys + '.nc'
print 'Opening ' + olrfile
# Check if OLR file exists for this model
if os.path.exists(olrfile):
### Open olr nc file
ncout = mync.open_multi(olrfile,globv,name,\
dataset=dset,subs=sub)
ndim = len(ncout)
if ndim == 5:
olr, time, lat, lon, dtime = ncout
elif ndim == 6:
olr, time, lat, lon, lev, dtime = ncout
olr = np.squeeze(olr)
else:
print 'Check number of levels in ncfile'
lat4sf = lat
lon4sf = lon
else:
print "No OLR data found for " + name
ys = moddct['yrfname']
### Open rain data - historical
print 'Getting historical rain data'
globp = 'pr'
raindset = dset
rainmod = name
rmoddct = moddct
rcal = cal
rys = ys
rainname = rmoddct['prname']
rainfile = botdir + raindset + "/" + rainmod + "." + globp + ".day.mean." + rys + ".nc"
print 'Opening ' + rainfile
rainout = mync.open_multi(rainfile, globp, rainmod, \
dataset=raindset, subs=sub)
rdim = len(rainout)
if rdim == 5:
rain, rtime, rlat, rlon, rdtime = rainout
elif rdim == 6:
rain, rtime, rlat, rlon, rlev, rdtime = rainout
rain = np.squeeze(rain)
else:
print 'Check number of levels in ncfile'
rdtime[:, 3] = 0
nlat = len(rlat)
nlon = len(rlon)
nboxes = float(nlat * nlon)
print 'Checking for duplicate timesteps' # do retain this - IPSL A LR has double tsteps
ys = '1950_2009'
else:
print 'variable ' + globv + ' has unclear yearname for ' + name2
else:
ys = moddct['fullrun']
# Open ltmonmean file
meanfile = bkdir + 'metbot_multi_dset/' + dset2 + '/' + name2 + '/' \
+ name2 + '.' + globv + '.mon.mean.' + ys + '.nc'
print meanfile
if os.path.exists(meanfile):
if levsel:
ncout = mync.open_multi(meanfile, globv, name2, \
dataset=dset2, subs=sub, levsel=levc)
else:
ncout = mync.open_multi(meanfile, globv, name2, \
dataset=dset2, subs=sub)
print '...file opened'
ndim = len(ncout)
if ndim == 5:
meandata, time, lat, lon, dtime = ncout
elif ndim == 6:
meandata, time, lat, lon, lev, dtime = ncout
meandata = np.squeeze(meandata)
else:
print 'Check number of dims in ncfile'
dtime[:, 3] = 0
# Fix lat and lons if it spans 0
print 'Subsetting by latitude?'
print 'Selecting CBs between ' + str(wlon) + ' and ' + str(elon)
dates_ln, cXs_ln, cYs_ln, degs_ln, chs_ln, keys_ln, daynos_ln, tworecdt_ln = \
sset.sel_cen_lon(wlon, elon, dates_dd, cXs_dd, cYs_dd, degs_dd, chs_dd, \
keys_dd, daynos_dd, tworecdt_dd)
# Second get info for mean rain
rys_clim = rys_clims[cent]
rainmeanfile = botdir + dset + '/' + name + '/' \
+ name + '.' + globp + '.mon.mean.' + rys_clim + '.nc'
print 'Opening ' + rainmeanfile
print 'for domain ' + pr_dom
rainmean = mync.open_multi(rainmeanfile, globp, name, \
dataset=dset, subs=pr_dom)
rdim = len(rainmean)
if rdim == 5:
rain_monmn, rtime, rlat_mn, rlon, rdtime_monmn = rainmean
elif rdim == 6:
rain, rtime, rlat_mn, rlon, rlev, rdtime_monmn = rainmean
rain_monmn = np.squeeze(rain)
else:
print 'Check number of levels in ncfile'
rdtime_monmn[:, 3] = 0
rainmons = rdtime_monmn[:, 1]
if weightlats:
latr = np.deg2rad(rlat_mn)
weights = np.cos(latr)
ys = '1950_2009'
else:
print 'variable ' + globv1 + ' has unclear yearname for ' + name2
else:
ys = moddct['fullrun']
# Open ltmonmean file
meanfile = bkdir + 'metbot_multi_dset/' + dset2 + '/' + name2 + '/' \
+ name2 + '.' + globv1 + '.mon.mean.' + ys + '.nc'
print 'Attempting to open ' + meanfile
if os.path.exists(meanfile):
if levsel1:
ncout = mync.open_multi(meanfile, globv1, name2, \
dataset=dset2, subs=sub_x, levsel=levc)
else:
ncout = mync.open_multi(meanfile, globv1, name2, \
dataset=dset2, subs=sub_x)
print '...file opened'
ndim = len(ncout)
if ndim == 5:
meandata, time, lat, lon, dtime = ncout
elif ndim == 6:
meandata, time, lat, lon, lev, dtime = ncout
meandata = np.squeeze(meandata)
else:
print 'Check number of dims in ncfile'
dtime[:, 3] = 0
# Remove duplicate timesteps
ys = refmoddct['yrfname']
# Open ltmonmean file
meanfile = botdir + refdset + '/' + refmod + '/' \
+ refmod + '.' + globv + '.mon.mean.' + ys + '.nc'
# Open with two different domains
doms = [dom_a, dom_b]
ndoms = len(doms)
seas_picks = [all_ttt_seas, per_ttt_seas]
reg_ref_means = np.zeros(ndoms, dtype=np.float32)
for do in range(ndoms):
thisdom = doms[do]
ths_seas = seas_picks[do]
ncout = mync.open_multi(meanfile, globv, refmod, \
dataset=refdset, subs=thisdom)
ndim = len(ncout)
if ndim == 5:
meandata, time, lat, lon, dtime = ncout
elif ndim == 6:
meandata, time, lat, lon, lev, dtime = ncout
meandata = np.squeeze(meandata)
dtime[:, 3] = 0
nlat = len(lat)
nlon = len(lon)
# Remove duplicate timesteps
print 'Checking for duplicate timesteps'
tmp = np.ascontiguousarray(dtime).view(
np.dtype((np.void, dtime.dtype.itemsize * dtime.shape[1])))
rawfile_u = bkdir + dset2 + '/' + name2 + \
'.' + globv1 + '.day.mean.' + gys + '.nc'
rawfile_v = bkdir + dset2 + '/' + name2 + \
'.' + globv2 + '.day.mean.' + gys + '.nc'
if variable == 'qflux':
rawfile_q = bkdir + dset2 + '/' + name2 + \
'.' + globv3 + '.day.mean.' + gys + '.nc'
print 'Opening ' + rawfile_u
print 'and corresponding file: ' + rawfile_v
if variable == 'qflux':
print 'and q file:' + rawfile_q
if levsel:
ncout_u = mync.open_multi(rawfile_u, globv1, name2, \
dataset=dset2, subs=subvar, levsel=levc)
ncout_v = mync.open_multi(rawfile_v, globv2, name2, \
dataset=dset2, subs=subvar, levsel=levc)
if variable == 'qflux':
ncout_q = mync.open_multi(rawfile_q, globv3, name2, \
dataset=dset2, subs=subvar, levsel=levc)
else:
ncout_u = mync.open_multi(rawfile_u, globv1, name2, \
dataset=dset2, subs=subvar)
ncout_v = mync.open_multi(rawfile_v, globv2, name2, \
dataset=dset2, subs=subvar)
if variable == 'qflux':
ncout_q = mync.open_multi(rawfile_q, globv3, name2, \
### Get saddle of distribution for ref dset (specified above)
moddct = dsetdict.dset_deets[refdset][refmod]
vname = moddct['olrname']
if testfile:
ys = moddct['testfileyr']
else:
ys = moddct['yrfname']
if testyear:
beginatyr = moddct['startyr']
else:
beginatyr = moddct['testyr']
indir = bkdir + "/" + refdset + "/"
infile = indir + refmod + ".olr.day.mean." + ys + ".nc"
print infile
ncout = mync.open_multi(infile, globv, refmod,\
dataset=refdset, subs=sub)
ndim = len(ncout)
if ndim == 5:
olr, time, lat, lon, dtime = ncout
elif ndim == 6:
olr, time, lat, lon, lev, dtime = ncout
olr = np.squeeze(olr)
else:
print 'Check number of levels in ncfile'
### Select data to run
### Get time information
units = moddct['olrtimeunit']
cal = moddct['calendar']
### If testfile run on all days available
if testfile:
meanfile_u = botdir + dset2 + '/' + name2 + '/' \
+ name2 + '.' + globv1 + '.mon.mean.' + ysclim + '.nc'
meanfile_v = botdir + dset2 + '/' + name2 + '/' \
+ name2 + '.' + globv2 + '.mon.mean.' + ysclim + '.nc'
if var == 'qflux':
meanfile_q = botdir + dset2 + '/' + name2 + '/' \
+ name2 + '.' + globv3 + '.mon.mean.' + ysclim + '.nc'
print 'Opening ' + meanfile_u
print 'and corresponding file: ' + meanfile_v
if var == 'qflux':
print 'and q file:' + meanfile_q
ncout_u = mync.open_multi(meanfile_u, globv1, name2, \
dataset=dset2, subs=sub, levsel=levc)
ncout_v = mync.open_multi(meanfile_v, globv2, name2, \
dataset=dset2, subs=sub, levsel=levc)
if var == 'qflux':
ncout_q = mync.open_multi(meanfile_q, globv3, name2, \
dataset=dset2, subs=sub, levsel=levc)
ndim = len(ncout_u)
if ndim == 5:
meandata_u, time, lat, lon, dtime = ncout_u
meandata_v, time, lat, lon, dtime = ncout_v
if var == 'qflux':
my.mkdir_p(outdir)
# Get info
moddct = dsetdict.dset_deets[dset][name]
vnamedict = globv + 'name'
varstr = moddct[vnamedict]
ys = moddct['yrfname']
dimdict = dim_exdict.dim_deets[globv][dset]
latname = dimdict[1]
lonname = dimdict[2]
# Open olr file
olrfile=botdir+dset+'/'+name+'.'+globv+\
'.day.mean.'+ys+'.nc'
print 'Opening ' + olrfile
ncout = mync.open_multi(olrfile, globv, name, \
dataset=dset, subs=sub)
ndim = len(ncout)
if ndim == 5:
olrdata, time, lat, lon, dtime = ncout
elif ndim == 6:
olrdata, time, lat, lon, lev, dtime = ncout
olrdata = np.squeeze(olrdata)
else:
print 'Check number of dims in ncfile'
dtime[:, 3] = 0
# print name
# print lon
# print lat
# # Fix lat and lons if it spans 0
