verticalmean.py

# coding=utf-8
from earthdiagnostics import cdftools
from earthdiagnostics.box import Box
from earthdiagnostics.diagnostic import Diagnostic
from earthdiagnostics.utils import Utils, TempFile


class VerticalMean(Diagnostic):
    """
    Chooses vertical level in ocean, or vertically averages between
    2 or more  ocean levels

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

    :created: February 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 to average
    :type variable: str
    :param box: box used to restrict the vertical mean
    :type box: Box
    """

    def __init__(self, data_manager, startdate, member, chunk, variable, box):
        Diagnostic.__init__(self, data_manager)
        self.startdate = startdate
        self.member = member
        self.chunk = chunk
        self.variable = variable
        self.box = box
        self.required_vars = [variable]
        self.generated_vars = [variable + 'vmean']

    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:
        """
        num_options = len(options) - 1
        if num_options < 1:
            raise Exception('You must specify the variable to average vertically')
        if num_options > 3:
            raise Exception('You must specify between one and three parameters for the vertical mean')
        variable = options[1]

        box = Box(True)
        if num_options >= 2:
            box.min_depth = float(options[2])
        if num_options >= 2:
            box.max_depth = float(options[3])

        job_list = list()
        for startdate, member, chunk in diags.exp_manager.get_chunk_list():
            job_list.append(VerticalMean(diags.data_manager, startdate, member, chunk,
                                         variable, box))
        return job_list

    def compute(self):
        """
        Runs the diagnostic
        """
        temp = TempFile.get()
        variable_file = self.data_manager.get_file('ocean', self.variable, self.startdate, self.member, self.chunk)

        handler = Utils.openCdf(variable_file)
        if self.box.min_depth is None:
            lev_min = handler.variables['lev'][0]
        else:
            lev_min = self.box.min_depth

        if self.box.max_depth is None:
            lev_max = handler.variables['lev'][-1]
        else:
            lev_max = self.box.max_depth
        handler.close()

        cdftools.run('cdfvertmean', input=variable_file, output=temp, options=[self.variable, 'T', lev_min, lev_max,
                                                                               '-debug'])
        Utils.setminmax(temp, '{0}_vert_mean'.format(self.variable))
        self.data_manager.send_file(temp, 'ocean', self.variable + 'vmean', self.startdate, self.member, self.chunk,
                                    box=self.box, rename_var='{0}_vert_mean'.format(self.variable))