# Copyright (c) 2023. Harvard University
#
# Developed by Research Software Engineering,
# Harvard University Research Computing and Data (RCD) Services.
#
# Author: Michael A Bouzinier
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#
"""
An entry point to aggregating grid data produced by
Atmospheric Composition Analysis Group of Washington
University in St. Louis.
The tool validates file names that they are using the naming pattern
employed by the group and infers year and month of the observations
from the file name.
`See data description: <https://sites.wustl.edu/acag/datasets/surface-pm2-5/>`_
"""
import logging
import os.path
import re
from typing import Dict
import yaml
from gridmet.netCDF_file_processor import NetCDFFile
from gridmet.config import GridContext
[docs]class WUSTLFile(NetCDFFile):
def __init__(self, context: GridContext = None):
"""
Creates a new instance
:param context: An optional GridmetContext object, if not specified,
then it is constructed from the command line arguments
"""
super().__init__(context)
self.year = None
self.month = None
return
[docs] def parse_file_name(self):
m = re.search("([1|2][0-9]{3}[0|1][0-9])_\\1", self.infile)
if m:
ym = m.group(1)
self.year = ym[:4]
self.month = ym[4:]
return
m = re.search("([1|2][0-9]{3})[0|1][0-9]_\\1[0|1][0-9]", self.infile)
if m:
ym = m.group(1)
self.year = ym[:4]
return
raise ValueError("File name: {} does not match expected pattern"
.format(self.infile))
[docs] def get_aggregation_year(self):
return self.year
[docs] def on_prepare(self):
if self.extra_columns is not None:
raise ValueError("For NetCDF files downloaded from WUSTL, extra columns cannot "
"be provided by user as they are calculated automatically")
self.parse_file_name()
if self.year is not None:
if self.month is not None:
self.extra_columns = ["Year", "Month"], [self.year, self.month]
else:
self.extra_columns = ["Year"], [self.year]
else:
self.extra_columns = None
return
[docs] def get_table_name(self):
if self.context.table is not None:
return super().get_table_name()
if self.year is None:
return super().get_table_name()
if self.context.variables:
v1 = self.context.variables[0]
if len(self.context.variables) > 1:
t = str(v1) + "_with_components"
else:
t = str(v1)
else:
return super().get_table_name()
if self.month is None:
t += "_annual"
else:
t += "_monthly"
if self.context.statistics:
t += "_" + self.context.statistics
return t
[docs] def get_registry(self) -> Dict:
d = os.path.dirname(__file__)
p = os.path.join(d, "models", self.get_domain_name() + ".yaml")
if os.path.isfile(p):
with open(p) as r:
logging.info(
"Retrieving data dictionary from: " + os.path.abspath(p)
)
registry = yaml.safe_load(r)
return registry
logging.info("Creating new generic data dictionary")
return super().get_registry()
if __name__ == '__main__':
task = WUSTLFile()
task.prepare()
task.execute()