averagesection.py

# coding=utf-8
import os
from earthdiagnostics.box import Box
from earthdiagnostics.diagnostic import *
from earthdiagnostics.utils import Utils, TempFile
from earthdiagnostics.modelingrealm import ModelingRealm


class AverageSection(Diagnostic):
    """
    Compute an average of a given zone. The variable MUST be in a regular grid

    :original author: Virginie Guemas <virginie.guemas@bsc.es>
    :contributor: Javier Vegas-Regidor<javier.vegas@bsc.es>

    :created: March 2012
    :last modified: June 2016

    :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 box: box to use for the average
    :type box: Box

    """

    alias = 'avgsection'
    "Diagnostic alias for the configuration file"

    def __init__(self, data_manager, startdate, member, chunk, domain, variable, box, grid):
        Diagnostic.__init__(self, data_manager)
        self.startdate = startdate
        self.member = member
        self.chunk = chunk
        self.variable = variable
        self.domain = domain
        self.box = box
        self.grid = grid

    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.box == other.box

    def __str__(self):
        return 'Average section Startdate: {0.startdate} Member: {0.member} Chunk: {0.chunk} Box: {0.box} ' \
               'Variable: {0.domain}:{0.variable} Grid: {0.grid}'.format(self)

    @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 longitude, maximum longitude, minimum latitude, maximum latitude, domain=ocean
        :type options: list[str]
        :return:
        """
        options_available = (DiagnosticDomainOption(),
                             DiagnosticVariableOption(),
                             DiagnosticIntOption('min_lon'),
                             DiagnosticIntOption('max_lon'),
                             DiagnosticIntOption('min_lat'),
                             DiagnosticIntOption('max_lat'),
                             DiagnosticOption('grid', ''))
        options = cls.process_options(options, options_available)
        box = Box()
        box.min_lon = options['min_lon']
        box.max_lon = options['max_lon']
        box.min_lat = options['min_lat']
        box.max_lat = options['max_lat']
        job_list = list()
        for startdate, member, chunk in diags.config.experiment.get_chunk_list():
            job_list.append(AverageSection(diags.data_manager, startdate, member, chunk,
                                           options['domain'], options['variable'], box, options['grid']))
        return job_list

    def request_data(self):
        self.variable_file = self.request_chunk(self.domain, self.variable, self.startdate, self.member, self.chunk,
                                                grid=self.grid)

    def declare_data_generated(self):
        self.mean = self.declare_chunk(self.domain, self.variable + 'mean', self.startdate, self.member, self.chunk,
                                       box=self.box, grid=self.grid)

    def compute(self):
        """
        Runs the diagnostic
        """
        temp = TempFile.get()
        variable_file = self.variable_file.local_file
        Utils.cdo.zonmean(input='-sellonlatbox,{0},{1},{2},{3} {4}'.format(self.box.min_lon, self.box.max_lon,
                                                                           self.box.min_lat, self.box.max_lat,
                                                                           variable_file),
                          output=temp)
        os.remove(variable_file)
        self.mean.set_local_file(temp, rename_var='tos')