def generate_dataset_report(folder):
'''
Generate a descriptive report on the data included in the use case.
:param folder: Path to the folder containing the NARCCAP example data.
:type folder: str
:returns: Path to the report file.
:rtype: str
'''
ocgis.env.DIR_DATA = folder
rds = parse_narccap_filenames(folder)
rdc = ocgis.RequestDatasetCollection(rds)
headers = ['DID', 'Filenames', 'Variable', 'Time Start', 'Time End']
(fd, name) = tempfile.mkstemp(suffix='.csv')
f = open(name, 'w')
writer = csv.writer(f)
writer.writerow(headers)
for rd in rdc:
logging.info(rd)
ds = NcDataset(rd)
to_write = [
rd.did, [os.path.split(uri)[1] for uri in rd.uri], rd.variable,
ds.temporal.value[0], ds.temporal.value[-1]
]
writer.writerow(to_write)
f.close()
return (name)
def generate_dataset_report(folder):
'''
Generate a descriptive report on the data included in the use case.
:param folder: Path to the folder containing the NARCCAP example data.
:type folder: str
:returns: Path to the report file.
:rtype: str
'''
ocgis.env.DIR_DATA = folder
rds = parse_narccap_filenames(folder)
rdc = ocgis.RequestDatasetCollection(rds)
headers = ['DID','Filenames','Variable','Time Start','Time End']
(fd,name) = tempfile.mkstemp(suffix='.csv')
f = open(name,'w')
writer = csv.writer(f)
writer.writerow(headers)
for rd in rdc:
logging.info(rd)
ds = NcDataset(rd)
to_write = [rd.did,
[os.path.split(uri)[1] for uri in rd.uri],
rd.variable,
ds.temporal.value[0],
ds.temporal.value[-1]]
writer.writerow(to_write)
f.close()
return(name)
def main():
## set to true to return smaller data slices - often good for debugging
snippet = False
## city center coordinate (~Austin, TX)
geom = [-97.74278,30.26694]
## directory to write output data. needs to exist!
ocgis.env.DIR_OUTPUT = '/tmp/narccap'
## location of directory containing climate data files
ocgis.env.DIR_DATA = '/usr/local/climate_data/narccap'
## write data to a common reference projection
ocgis.env.WRITE_TO_REFERENCE_PROJECTION = True
## pring additional information to console
ocgis.env.VERBOSE = True
## load the request datasets by parsing filenames on disk
rds = parse_narccap_filenames(ocgis.env.DIR_DATA)
## these are the calculations to perform
calc = [{'func':'mean','name':'mean'},
{'func':'median','name':'median'},
{'func':'max','name':'max'},
{'func':'min','name':'min'}]
## the temporal grouping to apply when performing the computations
calc_grouping = ['month','year']
## the operations object...
ops = ocgis.OcgOperations(dataset=rds,calc=calc,calc_grouping=calc_grouping,
output_format='csv+',geom=geom,abstraction='point',
snippet=snippet)
print(ops.execute())
def main():
## city center coordinate (~Austin, TX)
geom = [-97.74278, 30.26694]
## directory to write output data. needs to exist!
ocgis.env.DIR_OUTPUT = '/tmp/narccap'
## location of directory containing climate data files
ocgis.env.DIR_DATA = '/usr/local/climate_data/narccap'
## print additional information to console
ocgis.env.VERBOSE = True
## load the request datasets by parsing filenames on disk
rds = parse_narccap_filenames(ocgis.env.DIR_DATA)
## these are the calculations to perform
calc = [{'func': 'mean', 'name': 'mean'},
{'func': 'median', 'name': 'median'},
{'func': 'max', 'name': 'max'},
{'func': 'min', 'name': 'min'}]
## the temporal grouping to apply when performing the computations
calc_grouping = ['month', 'year']
## the operations object...
ops = ocgis.OcgOperations(dataset=rds, calc=calc, calc_grouping=calc_grouping,
output_format='csv+', geom=geom, abstraction='point',
output_crs=CFWGS84)
print(ops.execute())
def main():
## city center coordinate (~Austin, TX)
geom = [-97.74278,30.26694]
## directory to write output data. needs to exist!
ocgis.env.DIR_OUTPUT = '/tmp/narccap'
## location of directory containing climate data files
ocgis.env.DIR_DATA = '/usr/local/climate_data/narccap'
## print additional information to console
ocgis.env.VERBOSE = True
## load the request datasets by parsing filenames on disk
rds = parse_narccap_filenames(ocgis.env.DIR_DATA)
## these are the calculations to perform
calc = [{'func':'mean','name':'mean'},
{'func':'median','name':'median'},
{'func':'max','name':'max'},
{'func':'min','name':'min'}]
## the temporal grouping to apply when performing the computations
calc_grouping = ['month','year']
## the operations object...
ops = ocgis.OcgOperations(dataset=rds,calc=calc,calc_grouping=calc_grouping,
output_format='csv+',geom=geom,abstraction='point',
output_crs=CFWGS84)
print(ops.execute())
