def ftp_publications(self, cascade=False):
""" Return product generator. """
if isinstance(self.datetimes, (list, tuple)):
datetimes = self.datetimes
else:
# Generate datetimes from rangetext string.
datetimes = utils.MultiDateRange(self.datetimes).iterdatetimes()
combinations = utils.get_product_combinations(
datetimes=datetimes,
prodcodes=self.prodcodes,
timeframes=self.timeframes,
)
for combination in combinations:
nowcast = combination.pop('nowcast')
if nowcast != self.nowcast:
continue
if nowcast:
yield products.CopiedProduct(datetime=combination['datetime'])
continue
consistent = utils.consistent_product_expected(
prodcode=combination['prodcode'],
timeframe=combination['timeframe'],
)
product = products.CalibratedProduct(**combination)
if not consistent:
yield product
if cascade:
rps = products.Consistifier.get_rescaled_products(product)
for rescaled_product in rps:
yield rescaled_product
def rescale(**kwargs):
""" Create aggregates given some commandline arguments. """
# Determine action
task = tasks.rescale
if kwargs['direct']:
action = task
else:
action = task.delay
# Determine derived arguments
datetimes = utils.MultiDateRange(kwargs['range']).iterdatetimes()
combinations = utils.get_product_combinations(
datetimes=datetimes,
prodcodes=kwargs['prodcodes'],
timeframes=kwargs['timeframes'])
# Execute or delay task
for combination in combinations:
action_kwargs = dict(result=None,
direct=kwargs['direct'],
cascade=kwargs['cascade'])
rescale_kwargs = {
k: v
for k, v in combination.items()
if k in ['datetime', 'prodcode', 'timeframe']
}
action_kwargs.update(rescale_kwargs)
action(**action_kwargs)
def calibrate(**kwargs):
""" Create calibrated products given some commandline arguments. """
# Determine action
task = tasks.calibrate
if kwargs['direct']:
action = task
else:
action = task.delay
# Determine derived arguments
declutter = dict(
size=kwargs['declutter_size'],
history=kwargs['declutter_history'],
)
datetimes = utils.MultiDateRange(kwargs['range']).iterdatetimes()
combinations = utils.get_product_combinations(
datetimes=datetimes,
prodcodes=kwargs['prodcodes'],
timeframes=kwargs['timeframes'],
)
# Execute or delay task
for combination in combinations:
if kwargs['nowcast'] != combination['nowcast']:
continue
action_kwargs = dict(result=None,
declutter=declutter,
radars=kwargs['radars'],
direct=kwargs['direct'],
cascade=kwargs['cascade'])
action_kwargs.update(combination)
action(**action_kwargs)
def sandbox(**kwargs):
""" Print a value from various datafiles. """
i, j = map(int, kwargs['indices'].split(','))
datetimes = utils.MultiDateRange(kwargs['range']).iterdatetimes()
combinations = utils.get_product_combinations(
datetimes=datetimes,
prodcodes=kwargs['prodcodes'],
timeframes=kwargs['timeframes'],
)
for combination in combinations:
# The calibrate
calibrate = products.CalibratedProduct(**combination)
with calibrate.get() as calibrate_h5:
print('Calibrate: {}'.format(calibrate_h5['precipitation'][i, j]))
# The rescaled
if utils.consistent_product_expected(combination['prodcode'],
combination['timeframe']):
rescaled = products.ConsistentProduct(**combination)
print(rescaled.path)
with rescaled.get() as rescaled_h5:
print('Rescaled: {}'.format(rescaled_h5['precipitation'][i,
j], ))
# The thredds
thredds = products.ThreddsFile.get_for_product(calibrate)
t = thredds._index(calibrate)
with thredds.get() as thredds_h5:
print('Thredds: {}'.format(thredds_h5['precipitation'][i, j, t], ))
# The merged threddsfile
thredds_m = products.ThreddsFile.get_for_product(calibrate, merge=True)
t = thredds_m._index(calibrate)
with thredds_m.get() as thredds_m_h5:
print('Thredds(m): {} ({})'.format(
thredds_m_h5['precipitation'][i, j, t],
thredds_m_h5['available'][t]))
# Opendap
values = products.get_values_from_opendap(
x=i,
y=j,
start_date=combination['datetime'],
end_date=combination['datetime'],
)
print('Opendap: {}'.format(values))
def main():
""" Create images for a range of products. """
loghelper.setup_logging()
# Get products according to args
args = get_image_args()
multidaterange = utils.MultiDateRange(args['range'])
products = product_generator(product=args['product'],
prodcode=args['prodcode'],
timeframe=args['timeframe'],
datetimes=multidaterange.iterdatetimes(),
nowcast=args['nowcast'])
create = dict(png=images.create_png, tif=images.create_tif)[args['format']]
# Create images with those products
kwargs = args.copy()
map(kwargs.pop, ['range', 'product', 'timeframe', 'prodcode'])
create(products, **kwargs)