def concatenate_piControl(self, season=None, compressed=False):
experiment = "piControl"
fnames = sorted(
get_ensemble_filenames(self.variable, self.region, experiment))
#models=sorted(self.ensemble_dict.keys())
models = get_ok_models(self.region)
nmod = len(models)
ntimes = []
model_names = []
#Loop over without loading data to figure out the shortest length control run
for model in models:
# print(model)
I = np.where([x.split(".")[2] == model for x in fnames])[0]
if len(I) > 0:
first_member = int(I[0])
fname = fnames[first_member]
model_names += [fname]
f = cdms.open(fname)
ntimes += [int(f[self.variable].shape[0])]
f.close()
L = np.min(ntimes)
#Set the time axis to be the time axis of the shortest control rin
imin = np.argmin(ntimes)
fshortest = model_names[imin]
f = cdms.open(fshortest)
tax = f(self.variable).getTime()
tax.id = 'time'
tax.designateTime()
f.close()
#Load data
#SingleMember=np.ma.zeros((len(model_names),L))+1.e20
SingleMember = np.ma.zeros((nmod, L)) + 1.e20
i = 0
for model in models:
I = np.where([x.split(".")[2] == model for x in fnames])[0]
if len(I) > 0:
first_member = I[0]
fname = fnames[first_member]
f = cdms.open(fname)
vdata = f(self.variable)
SingleMember[i] = vdata[:L]
i += 1
else:
if self.verbose:
print("No piControl data for " + model + " " +
self.variable)
f.close()
#Historical units are already converted; need to convert piControl from
#kg m-2 s-1 to mm day-1
#if self.variable in ["pr","evspsbl","prsn","mrros","mrro"]:
# SingleMember = SingleMember*86400.
SingleMember = MV.masked_where(
np.abs(SingleMember) > 1.e10, SingleMember)
SingleMember = MV.array(SingleMember)
SingleMember.setAxis(1, tax)
SingleMember.setAxis(0, cmip5.make_model_axis(models))
###KLUDGE: FIRST YEAR IS ZERO- FIX THIS IN DOWNLOADER
SingleMember = MV.masked_where(SingleMember == 0, SingleMember)
# if self.variable in ["mrsos","mrso"]:
# if not raw:
# SingleMember=self.standardize_zscore(SingleMember)
# else:
# if not raw:
# SingleMember=self.convert_to_percentage(SingleMember)
if season is None:
return SingleMember
cdutil.setTimeBoundsMonthly(SingleMember)
seasonal = getattr(cdutil, season).departures(SingleMember)
return DA_tools.concatenate_this(seasonal, compressed=compressed)
def __init__(self, experiment):
self.experiment = experiment
f = cdms.open("DATA/cmip5.sahel_precip." + experiment + ".nc")
west = f("pr_W")
east = f("pr_CE")
self.data = {}
self.data["west"] = west
self.data["east"] = east
west_a = cdutil.ANNUALCYCLE.departures(west)
east_a = cdutil.ANNUALCYCLE.departures(east)
if experiment != "piControl":
nmod, nmon = west_a.shape
west_rs = west_a.reshape((nmod, nmon / 12, 12))
west_rs.setAxis(0, west.getAxis(0))
tax = cdms.createAxis(west.getTime()[6::12])
tax.id = 'time'
tax.designateTime()
tax.units = west.getTime().units
west_rs.setAxis(1, tax)
westsolver = Eof(MV.average(west_rs, axis=0))
else:
west_a = da.concatenate_this(west_a, compressed=True)
nmon, = west_a.shape
tax = cdms.createAxis(np.arange(west_a.shape[0]))
tax.units = 'months since 0001-1-15'
tax.id = 'time'
tax.designateTime()
taxC = tax.asComponentTime()
test = [x.torel('days since 0001-1-15').value for x in taxC]
tax_days = cdms.createAxis(test)
tax_days.designateTime()
tax_days.id = 'time'
tax_days.units = 'days since 0001-1-15'
west_a.setAxis(0, tax_days)
taxmonthly = cdms.createAxis(west_a.getTime()[6::12])
taxmonthly.units = west_a.getTime().units
taxmonthly.designateTime()
taxmonthly.id = 'time'
west_rs = west_a.reshape((nmon / 12, 12))
west_rs.setAxis(0, taxmonthly)
westsolver = Eof(west_rs)
if experiment != "piControl":
nmod, nmon = east_a.shape
east_rs = east_a.reshape((nmod, nmon / 12, 12))
east_rs.setAxis(0, east.getAxis(0))
east_rs.setAxis(1, tax)
eastsolver = Eof(MV.average(east_rs, axis=0))
else:
east_a = da.concatenate_this(east_a, compressed=True)
east_a.setAxis(0, tax_days)
nmon, = east_a.shape
east_rs = east_a.reshape((nmon / 12, 12))
east_rs.setAxis(0, taxmonthly)
eastsolver = Eof(east_rs)
facwest = da.get_orientation(westsolver)
faceast = da.get_orientation(eastsolver)
self.solvers = {}
self.solvers["east"] = eastsolver
self.solvers["west"] = westsolver
self.reshaped = {}
self.reshaped["east"] = east_rs
self.reshaped["west"] = west_rs
if len(self.reshaped["west"].shape) > 2:
data = [
MV.average(cmip5.ensemble2multimodel(self.reshaped["west"]),
axis=0),
MV.average(cmip5.ensemble2multimodel(self.reshaped["east"]),
axis=0)
]
else:
data = [self.reshaped["west"], self.reshaped["east"]]
msolver = MultivariateEof(data)
self.solvers["multi"] = msolver
self.anomalies = {}
self.anomalies["east"] = east_a
self.anomalies["west"] = west_a