def Forward(rcf, verbosity='INFO'):
# Set verbosity level
logger.setLevel(verbosity)
# Read config
rcf = rc(rcf)
start = datetime(*rcf.get('time.start'))
end = datetime(*rcf.get('time.end'))
# Read observations
obsfile = rcf.get('observations.filename')
db = obsdb(filename=obsfile)
db.setupFootprints(path=rcf.get('footprints.path'),
cache=rcf.get('footprints.cache'))
# Read fluxes
categories = dict.fromkeys(rcf.get('emissions.categories'))
for cat in categories:
categories[cat] = rcf.get(f'emissions.{cat}.origin')
emis = lagrange.ReadArchive(rcf.get('emissions.prefix'),
start,
end,
categories=categories)
# transport model run
model = lumia.transport(rcf, obs=db, formatter=lagrange)
model.runForward(struct=emis, step=rcf.get('tag'))
return model
def _from_hdf(self, filename, loadrc=True):
self.vectors = read_hdf(filename, 'vectors')
with h5py.File(filename, 'r') as fid:
# rcf
if loadrc:
rcf = rc()
for key in fid['rcf'].attrs:
rcf.setkey(key, fid['rcf'].attrs[key])
else:
try:
rcf = self.rcf
except AttributeError:
logger.critical("no rcf info in the object")
raise
# correlations :
for cor in fid['correlations/hor']:
self.horizontal_correlations[cor] = fid['correlations/hor'][
cor][:]
for cor in fid['correlations/temp']:
self.temporal_correlations[cor] = fid['correlations/temp'][
cor][:]
return rcf
def __init__(self, rcf, obs, emfile, mp=False, checkfile=None):
self.rcf = rctools.rc(rcf)
self.obs = obsdb(obs)
self.obs.checkIndex(reindex=True)
self.obsfile = obs
self.rcfile = rcf
self.emfile = emfile
self.executable = __file__
self.batch = os.environ['INTERACTIVE'] == 'F'
self.categories = Categories(self.rcf)
self.checkfile=checkfile
logger.debug(checkfile)
if mp :
self.parallel = True
self.runForward = self.runForward_mp
self.runAdjoint = self.runAdjoint_mp
else :
self.parallel = False
self.runForward = self.runForward_sp
self.runAdjoint = self.runAdjoint_sp