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# coding=utf-8
import os
from earthdiagnostics.diagnostic import Diagnostic, DiagnosticOption, DiagnosticDomainOption, \
DiagnosticFrequencyOption, DiagnosticVariableOption
from earthdiagnostics.frequency import Frequencies
from earthdiagnostics.utils import TempFile, Utils
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class TimeMean(Diagnostic):
"""
Base class for all time mean diagnostics
:param data_manager: data management object
:type data_manager: DataManager
:param startdate: startdate
:type startdate: str
:param member: member number
:type member: int
:param chunk: chunk's number
:type chunk: int
:param variable: variable's name
:type variable: str
:param domain: variable's domain
:type domain: ModelingRealm
:param frequency: original frequency
:type frequency: str
:param grid: original data grid
:type grid: str
"""
def __init__(self, data_manager, startdate, member, chunk, domain, variable, frequency, grid):
Diagnostic.__init__(self, data_manager)
self.startdate = startdate
self.member = member
self.chunk = chunk
self.variable = variable
self.domain = domain
self.frequency = frequency
self.grid = grid
self._target_frequency = None
def __str__(self):
return 'Calculate {0._target_frequency} mean Startdate: {0.startdate} Member: {0.member} Chunk: {0.chunk} ' \
'Variable: {0.domain}:{0.variable} Original frequency: {0.frequency} Grid: {0.grid}'.format(self)
def __eq__(self, other):
return self.startdate == other.startdate and self.member == other.member and self.chunk == other.chunk and \
self.domain == other.domain and self.variable == other.variable and self.frequency == other.frequency and \
self.grid == other.grid and self._target_frequency == other._target_frequency
@classmethod
def _process_options(cls, diags, options):
options_available = (DiagnosticDomainOption(),
DiagnosticVariableOption(diags.data_manager.config.var_manager),
DiagnosticFrequencyOption(),
DiagnosticOption('grid', ''))
options = cls.process_options(options, options_available)
return options
@classmethod
def generate_jobs(cls, diags, options):
"""
Create a job for each chunk to compute the diagnostic
:param diags: Diagnostics manager class
:type diags: Diags
:param options: variable, domain, frequency=day, grid=''
:type options: list[str]
:return:
"""
options = cls._process_options(diags, options)
job_list = list()
for startdate, member, chunk in diags.config.experiment.get_chunk_list():
job_list.append(cls(diags.data_manager, startdate, member, chunk,
options['domain'], options['variable'], options['frequency'], options['grid']))
return job_list
def request_data(self):
"""Request data required by the diagnostic"""
self.variable_file = self.request_chunk(self.domain, self.variable, self.startdate, self.member, self.chunk,
frequency=self.frequency, grid=self.grid)
def declare_data_generated(self):
"""Declare data to be generated by the diagnostic"""
self.daymean = self.declare_chunk(self.domain, self.variable, self.startdate, self.member, self.chunk,
frequency=Frequencies.daily, grid=self.grid)
def compute_mean(self, input_file, output_file):
Parameters
----------
input_file: str
output_file: str
"""
raise NotImplementedError()
def compute(self):
"""Run the diagnostic"""
temp = TempFile.get()
handler = Utils.open_cdf(self.variable_file.local_file)
if 'region' in handler.variables:
noregion = TempFile.get()
Utils.nco.ncks(input=self.variable_file.local_file, output=noregion, options=('-O -C -x -v region',))
self.compute_mean(noregion, temp)
os.remove(noregion)
monmean_handler = Utils.open_cdf(temp)
Utils.copy_variable(handler, monmean_handler, 'region')
monmean_handler.close()
else:
self.compute_mean(self.variable_file.local_file, temp)
self.daymean.set_local_file(temp)
class DailyMean(TimeMean):
"""
Calculates daily mean for a given variable
:param data_manager: data management object
:type data_manager: DataManager
:param startdate: startdate
:type startdate: str
:param member: member number
:type member: int
:param chunk: chunk's number
:type chunk: int
:param variable: variable's name
:type variable: str
:param domain: variable's domain
:type domain: ModelingRealm
:param frequency: original frequency
:type frequency: str
:param grid: original data grid
:type grid: str
"""
alias = 'daymean'
"Diagnostic alias for the configuration file"
def __init__(self, data_manager, startdate, member, chunk, domain, variable, frequency, grid):
TimeMean.__init__(self, data_manager, startdate, member, chunk, domain, variable, frequency, grid)
self._target_frequency = 'daily'
def compute_mean(self, input_file, output_file):
Parameters
----------
input_file: str
output_file: str
Utils.cdo.daymean(input=input_file, output=output_file)
class MonthlyMean(TimeMean):
"""
Calculates monthly mean for a given variable
:param data_manager: data management object
:type data_manager: DataManager
:param startdate: startdate
:type startdate: str
:param member: member number
:type member: int
:param chunk: chunk's number
:type chunk: int
:param variable: variable's name
:type variable: str
:param domain: variable's domain
:type domain: ModelingRealm
:param frequency: original frequency
:type frequency: str
:param grid: original data grid
:type grid: str
"""
alias = 'monmean'
"Diagnostic alias for the configuration file"
def __init__(self, data_manager, startdate, member, chunk, domain, variable, frequency, grid):
TimeMean.__init__(self, data_manager, startdate, member, chunk, domain, variable, frequency, grid)
self._target_frequency = 'monthly'
def compute_mean(self, input_file, output_file):
Parameters
----------
input_file: str
output_file: str
Utils.cdo.monmean(input=input_file, output=output_file)
class YearlyMean(TimeMean):
"""
Calculates monthly mean for a given variable
:param data_manager: data management object
:type data_manager: DataManager
:param startdate: startdate
:type startdate: str
:param member: member number
:type member: int
:param chunk: chunk's number
:type chunk: int
:param variable: variable's name
:type variable: str
:param domain: variable's domain
:type domain: ModelingRealm
:param frequency: original frequency
:type frequency: str
:param grid: original data grid
:type grid: str
"""
alias = 'yearmean'
"Diagnostic alias for the configuration file"
def __init__(self, data_manager, startdate, member, chunk, domain, variable, frequency, grid):
TimeMean.__init__(self, data_manager, startdate, member, chunk, domain, variable, frequency, grid)
self._target_frequency = 'yearly'
def compute_mean(self, input_file, output_file):
Parameters
----------
input_file: str
output_file: str
Utils.cdo.monmean(input=input_file, output=output_file)