def plot_allregions(ptype='nh'):
""" plot_allregions(ptype='nh'): plot all defined regions
"""
regdict = con.get_regiondict()
nreg = len(regdict)
rem = np.mod(nreg,2)
rows = 2
if rem==0:
cols = nreg/rows
else:
cols = nreg/rows + rem # rem will always be 1 if dividing by 2
if cols>8:
rows = 3
cols = nreg/rows + np.mod(nreg,rows)/2
print 'nrows: ' + str(rows) + ' ncols: ' + str(cols) # @@@
lat = con.get_t63lat()
lon = con.get_t63lon()
fig,spax = plt.subplots(rows,cols)
fig.set_size_inches(cols*2,rows*3)
for aii,ax in enumerate(spax.flat):
dummy = con.get_t63landmask() # dummy data
regkey = regdict.keys()[aii]
limsdict = regdict[regkey]
# mask the dummy data
dummym,dmask = cutl.mask_region(dummy,lat,lon,regkey,limsdict=limsdict)
kemmap(dummym,lat,lon,ptype=ptype,axis=ax,suppcb=1,cmin=-11,cmax=2,cmap='blue2blue_w10')
ax.set_title(regkey)
ax.set_xlabel(str(limsdict['latlims']) + ',' +str(limsdict['lonlims']) )
if aii==nreg-1: break # get out of loop if done with regions
fnamec, fnamep = con.build_filepathpair(sim, field)
fldc = cnc.getNCvar(fnamec, ncfield, seas=sea)
fldp = cnc.getNCvar(fnamep, ncfield, seas=sea)
lon = cnc.getNCvar(fnamec, "lon")
lat = cnc.getNCvar(fnamec, "lat")
fldca = np.squeeze(fldc - np.mean(fldc, axis=0)) # remove time mean
fldpa = np.squeeze(fldp - np.mean(fldp, axis=0))
if subset:
msk1 = con.get_t63regionmask("other", limsdict=limsdict)
fldca, msk = cutl.mask_region(fldca, lat, lon, "other", limsdict=limsdict)
fldpa, msk = cutl.mask_region(fldpa, lat, lon, "other", limsdict=limsdict)
oshape = fldca.shape # original shape
print fldca.shape
fldca1 = fldca[~fldca.mask] # @@@ why do I have to invert it. so dumb.
# fldca2=fldca[msk]
fldpa1 = fldpa[~fldpa.mask]
nshape = fldca1.shape # new shape
print fldca1.shape
# print fldca2.shape
# only keep region of interest?
lato = lat
def load_ncfield(field, ncfield, zonal=True,conv=1,mo=0,season=None,last='last100',includeyr1=False,verb=False):
"""
If zonal=True, compute zonal mean.
zonal can also be a region, defined in regiondict in constants.py
returns dictionaries: full field w/ time, zonal mean w/ time
"""
timepers,timesels = get_timeinfo(last,includeyr1)
seasonalizedt = {'mo':mo, 'season': season}
ncflddt={}; ncfldtmdt={}; ncfldzmdt={}
for casename in casenames:
fname= basedir + casename +'/ts/' + casename + '_' + field + '_' + timepers[casename] + '_ts.nc'
timesel=timesels[casename]
if verb:
print fname
try:
fld=cnc.getNCvar(fname,ncfield,timesel=timesel)*conv # remlon not operational??? why commented out??
if verb:
print fname + ', fld.shape ' + str(fld.shape) # @@@
except IOError as rte: # previously this was a RuntimeError. Not sure what changed. 10/14/2016
print rte
if 'No such file or directory' in rte.args:
# Here the problem is most likely that pico2ipulse filename fails b/c
# there is no NH version of it (for when last200=True). Remove the NH and try again.
# @@ Of course this could be a problem too b/c now we have full globe for just this run.
if field[-2:] != 'NH':
print 'not an NH versus global problem...File really not found'
raise
fname= basedir + casename +'/ts/' + casename + '_' + field[:-2] + '_' + timepers[casename] + '_ts.nc'
print 'Try again: ' + fname
fld=cnc.getNCvar(fname,ncfield,timesel=timesel)*conv
tmplat=cnc.getNCvar(fname,'lat')
if last=='last200': # how to tell which spot lat is?
if zonal: # then it is likely time x lat x lon
#print 'zonal is true. fld dims? ' + str(fld.shape)
fld=fld[...,tmplat>0,:]
else: # likely time x lev x lat
fld=fld[...,tmplat>0]
else:
raise
# just get the full timeseries, and zonal mean if asked.
if 1: #timeseries: # do not time average (actually save time average anyway)
if (season==None and mo==0):
pass
else:
fld = cutl.seasonalize(fld,**seasonalizedt)
#fldtm = fld
# zonal average
if zonal==True:
fldzm = fld[...,:-1].mean(axis=2) # remove extra lon
elif zonal in con.get_regiondict().keys():
print 'lat,lon shapes ' + str(lat.shape),str(lon.shape)
tempo, _ = cutl.mask_region(fld,lat,lon,region=zonal)
fldzm = tempo.mean(axis=2)
else:
fldzm = None
#fldtm = fldtmzm.mean(axis=0)
# else:
# # seasonal & time mean
# fldtm = np.mean(cutl.seasonalize(fld,**seasonalizedt),axis=0)
# # zonal average
# if zonal:
# fldtmzm = fldtm[...,:-1].mean(axis=1)
# elif zonal in con.get_regiondict().keys():
# tempo, _ = cutl.mask_region(fldtm,lat,lon,region=zonal)
# fldtmzm = tempo.mean(axis=1)
# else:
# fldtmzm = fldtm
print 'fld.shape: ' + str(fld.shape)
if fldzm!=None:
print 'fldzm.shape: ' + str(fldzm.shape)
ncflddt[casename] = fld # keep all dims
#ncfldtmdt[casename] = fldtm # time mean
ncfldzmdt[casename] = fldzm # zonal mean (w/ time dim)
return ncflddt, ncfldzmdt
def load_ncfield(field, ncfield, zonal=True,conv=1,mo=0,season=None,last='last100',
includeyr1=False,verb=False,local=False,seacyc=False,pulse=False):
"""
If zonal=True, compute zonal mean.
zonal can also be a region, defined in regiondict in constants.py
If local, use local data (which is limited)
If seacycle, return the 12 month climo average, which only exists
1. locally (as of Mar 24 2017) and 2. is only avail for the last200
returns dictionaries: full field w/ time, zonal mean w/ time
"""
timepers,timesels = get_timeinfo(last,includeyr1)
if local:
#bd='/Users/kelly/DropboxWork/UWashCanSISE/DATA/relaxationruns/' #limited fields here
bd='/Users/kelly/DATA/DataDisk/' # limited but not shared so there are more data
subdir='/'
else:
bd=basedir
subdir='/ts/'
seasonalizedt = {'mo':mo, 'season': season}
ncflddt={}; ncfldtmdt={}; ncfldzmdt={}
for casename in casenames:
if pulse==False and ('pulse' in casename): continue
if seacyc:
if last!='last200':
raise Exception('load_ncfield(): if seacyc=True, last must = last200')
if local!=True:
raise Exception('load_ncfield(): if seacyc=True, local must be True (as of Mar 24 2017)')
fname = bd + casename+subdir+casename + '_' + field + '_' + timepers[casename] + '_seacycle.nc'
else:
fname= bd + casename +subdir + casename + '_' + field + '_' + timepers[casename] + '_ts.nc'
timesel=timesels[casename]
if verb:
print fname
try:
fld=cnc.getNCvar(fname,ncfield,timesel=timesel)*conv # remlon not operational??? why commented out??
if verb:
print fname + ', fld.shape ' + str(fld.shape) # @@@
except IOError as rte: # previously this was a RuntimeError. Not sure what changed. 10/14/2016
print rte
if 'No such file or directory' in rte.args:
# Here the problem is most likely that pico2ipulse filename fails b/c
# there is no NH version of it (for when last200=True). Remove the NH and try again.
# @@ Of course this could be a problem too b/c now we have full globe for just this run.
if field[-2:] != 'NH':
print 'not an NH versus global problem...File really not found'
raise
fname= basedir + casename +'/ts/' + casename + '_' + field[:-2] + '_' + timepers[casename] + '_ts.nc'
print 'Try again: ' + fname
fld=cnc.getNCvar(fname,ncfield,timesel=timesel)*conv
tmplat=cnc.getNCvar(fname,'lat')
if last=='last200': # how to tell which spot lat is?
if zonal: # then it is likely time x lat x lon
#print 'zonal is true. fld dims? ' + str(fld.shape)
fld=fld[...,tmplat>0,:]
else: # likely time x lev x lat
fld=fld[...,tmplat>0]
else:
raise
# just get the full timeseries, and zonal mean if asked.
if 1: #timeseries: # do not time average (actually save time average anyway)
if (season==None and mo==0):
pass
else:
fld = cutl.seasonalize(fld,**seasonalizedt)
#fldtm = fld
# zonal average
if zonal==True:
fldzm = fld[...,:-1].mean(axis=2) # remove extra lon
elif zonal in con.get_regiondict().keys():
print 'lat,lon shapes ' + str(lat.shape),str(lon.shape)
tempo, _ = cutl.mask_region(fld,lat,lon,region=zonal)
fldzm = tempo.mean(axis=2)
else:
fldzm = None
#fldtm = fldtmzm.mean(axis=0)
# else:
# # seasonal & time mean
# fldtm = np.mean(cutl.seasonalize(fld,**seasonalizedt),axis=0)
# # zonal average
# if zonal:
# fldtmzm = fldtm[...,:-1].mean(axis=1)
# elif zonal in con.get_regiondict().keys():
# tempo, _ = cutl.mask_region(fldtm,lat,lon,region=zonal)
# fldtmzm = tempo.mean(axis=1)
# else:
# fldtmzm = fldtm
print 'fld.shape: ' + str(fld.shape)
if fldzm!=None:
print 'fldzm.shape: ' + str(fldzm.shape)
ncflddt[casename] = fld # keep all dims
#ncfldtmdt[casename] = fldtm # time mean
ncfldzmdt[casename] = fldzm # zonal mean (w/ time dim)
# try this: add coords # @@@@@@@@@@
lat,lon = load_nclatlon(field,last=last,includeyr1=includeyr1,verb=verb,local=local)
ncflddt['lat'] = lat; ncflddt['lon'] = lon;
try:
lev = load_nclev(field,last=last,includeyr1=includeyr1,verb=verb)
ncflddt['lev'] = lev
except:
print "No lev coord. Leave it"
ncfldzmdt['lat'] = lat
return ncflddt, ncfldzmdt