def run(self, args):
print 'OCG args=%s' % args
# apply time_range and time_region constraints to each dataset
for dataset in args['datasets']:
dataset['time_range'] = args['time_range']
dataset['time_region'] = args['time_region']
del args['time_range']
del args['time_region']
print 'Running OCGIS job with arguments=%s' % args
# fake invocation on laptop
if self.debug:
time.sleep(SLEEP_SECONDS)
download_path = "/usr/NCPP/static/ocgis/ocgis_output/MaurerNew_ARRM-CGCM3_bias_tasmax_mean_mon1_1971-2000_US48.jpg"
# real invocation on NOAA servers
else:
import ocgis
# create output directory
dir_output = os.path.join(self.rootDir, args['dir_output'])
# remove existing directory, generated by previous installation
if os.path.exists(dir_output):
rmtree(dir_output)
# generate empty directory
os.makedirs(dir_output)
# build up the list of request datasets
print "ocgis.RequestDatasetCollection(args['datasets']): %s" % args['datasets']
datasets = ocgis.RequestDatasetCollection(args['datasets'])
## construct the operations call
ops = ocgis.OcgOperations(dataset=datasets,
geom=args['geom'],
select_ugid=args['select_ugid'],
agg_selection=args['agg_selection'],
aggregate=args['aggregate'],
spatial_operation=args['spatial_operation'],
calc=args['calc'],
calc_grouping=args['calc_grouping'],
calc_raw=args['calc_raw'],
prefix=args['prefix'],
output_format=args['output_format'],
dir_output=dir_output,
headers=args['headers'])
# execute the operation
# 'path' points to the top-level folder containing the output data
path = ops.execute()
# 'download_path' points to single file for user to download
download_path = ocgis.format_return(path, ops, with_auxiliary_files=args['with_auxiliary_files'])
# return ouput
url = download_path.replace(self.rootDir, self.rootUrl)
return url
def run(self, args):
print 'Running OCGIS job with arguments=%s' % args
# fake invocation on laptop
if self.debug:
time.sleep(SLEEP_SECONDS)
download_path = "/usr/NCPP/static/ocgis/ocgis_output/MaurerNew_ARRM-CGCM3_bias_tasmax_mean_mon1_1971-2000_US48.jpg"
# real invocation on NOAA servers
else:
import ocgis
# create output directory
dir_output = os.path.join(self.rootDir, args['dir_output'])
# remove existing directory, generated by previous installation
if os.path.exists(dir_output):
rmtree(dir_output)
# generate empty directory
os.makedirs(dir_output)
# build up the list of request datasets
'''
datasets = []
iter_tuple = [args[key] for key in ['uri', 'variable', 't_calendar', 't_units', 'alias']]
time_range=args['time_range']
time_region=args['time_region']
for uri,variable,t_calendar,t_units,alias in zip(*iter_tuple):
rd = ocgis.RequestDataset(uri=uri,variable=variable,t_calendar=t_calendar,t_units=t_units,
time_range=time_range,time_region=time_region,alias=alias)
datasets.append(rd)
'''
datasets = ocgis.RequestDatasetCollection(args['datasets'])
## construct the operations call
ops = ocgis.OcgOperations(dataset=datasets,
geom=args['geom'],
select_ugid=args['select_ugid'],
agg_selection=args['agg_selection'],
aggregate=args['aggregate'],
spatial_operation=args['spatial_operation'],
calc=args['calc'],
calc_grouping=args['calc_grouping'],
calc_raw=args['calc_raw'],
prefix=args['prefix'],
output_format=args['output_format'],
dir_output=dir_output,
headers=args['headers'])
# execute the operation
# 'path' points to the top-level folder containing the output data
path = ops.execute()
# 'download_path' points to single file for user to download
download_path = ocgis.format_return(path, ops, with_auxiliary_files=args['with_auxiliary_files'])
# return ouput
url = download_path.replace(self.rootDir, self.rootUrl)
return url
