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# coding=utf-8
from earthdiagnostics import cdftools
from earthdiagnostics.box import Box
from earthdiagnostics.diagnostic import Diagnostic, DiagnosticOption, DiagnosticIntOption, DiagnosticDomainOption
from earthdiagnostics.utils import Utils, TempFile
from earthdiagnostics.modelingrealm import ModelingRealms
class RegionMean(Diagnostic):
"""
Chooses vertical level in ocean, or vertically averages between
2 or more ocean levels
:original author: Javier Vegas-Regidor <javier.vegas@bsc.es>
:created: January 2017
: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 to average
:type variable: str
:param box: box used to restrict the vertical mean
:type box: Box
"""
alias = 'regmean'
"Diagnostic alias for the configuration file"
def __init__(self, data_manager, startdate, member, chunk, domain, variable, grid, box):
Diagnostic.__init__(self, data_manager)
self.startdate = startdate
self.member = member
self.chunk = chunk
self.domain = domain
self.variable = variable
self.grid = grid.upper()
self.box = box
self.required_vars = [variable]
self.generated_vars = [variable + 'vmean']
def __eq__(self, other):
return self.startdate == other.startdate and self.member == other.member and self.chunk == other.chunk and \
self.box == other.box and self.variable == other.variable
def __str__(self):
return 'Vertical mean Startdate: {0} Member: {1} Chunk: {2} Variable: {3} ' \
'Box: {4}'.format(self.startdate, self.member, self.chunk, self.variable, self.box)
@classmethod
def generate_jobs(cls, diags, options):
"""
Creates a job for each chunk to compute the diagnostic
:param diags: Diagnostics manager class
:type diags: Diags
:param options: variable, minimum depth (level), maximum depth (level)
:type options: list[str]
:return:
"""
options_available = (DiagnosticDomainOption('domain'),
DiagnosticOption('variable'),
DiagnosticOption('grid'),
DiagnosticIntOption('min_depth', -1),
DiagnosticIntOption('max_depth', -1))
options = cls.process_options(options, options_available)
box = Box()
if options['min_depth'] >= 0:
box.min_depth = options['min_depth']
if options['max_depth'] >= 0:
box.max_depth = options['max_depth']
job_list = list()
for startdate, member, chunk in diags.config.experiment.get_chunk_list():
job_list.append(RegionMean(diags.data_manager, startdate, member, chunk,
options['domain'], options['variable'], options['grid'], box))
return job_list
def compute(self):
"""
Runs the diagnostic
"""
temp = TempFile.get()
variable_file = self.data_manager.get_file(self.domain, self.variable, self.startdate, self.member, self.chunk)
cdftools.run('cdfmean', input=variable_file, output=temp, options=[self.domain, self.variable, 'T', 0, 0, 0, 0,
self.box.min_depth, self.box.max_depth])
Utils.setminmax(temp, 'mean_{0}'.format(self.variable))
self.send_file(temp, ModelingRealms.ocean, self.variable + 'mean', self.startdate, self.member, self.chunk,
box=self.box, rename_var='mean_{0}'.format(self.variable))