Source code for pycif.plugins.datastreams.fluxes.chimere.read

import datetime
import os

import numpy as np
import xarray as xr
import resource

from .....utils.netcdf import readnc




def read(
        self,
        name,
        varnames,
        dates,
        files,
        interpol_flx=False,
        tracer=None,
        model=None,
        ddi=None,
        **kwargs
):
    """Get fluxes from pre-computed fluxes and load them into a pyCIF
    variables

    Args:
        self: the fluxes Plugin
        name: the name of the component
        tracdir, tracfile: flux directory and file format
        dates: list of dates to extract
        interpol_flx (bool): if True, interpolates fluxes at time t from
        values of surrounding available files

    """

    var2extract = varnames if varnames != "" else name

    # Reading required fluxes files
    trcr_flx = []
    for period, ff in zip(dates, files):
        ds = xr.open_dataset(ff)

        # Force conversion to float64
        data = ds[var2extract].values.astype(float)

        # Get the correct hour in the file
        if ddi is not None:
            hour = int((period[0] - ddi).total_seconds() // 3600)

        else:
            if "Times" not in ds:
                raise Exception("Times variables is not available and I have "
                                "no information on the file date")

            times = ds["Times"].values
            times = [
                datetime.datetime.strptime(
                    str(b"".join(s), "utf-8"), "%Y-%m-%d_%H:%M:%S"
                )
                for s in times
            ]
            hour = int((period[0] - times[0]).total_seconds() // 3600)

        # Scale the diurnal cycle
        if hasattr(tracer, "diurnal_factor"):
            data = tracer.diurnal_factor * data \
                   + (1 - tracer.diurnal_factor) * data.mean(axis=0)

        trcr_flx.append(data[hour, ...])
    
    # Building a xarray
    xmod = xr.DataArray(
        trcr_flx, coords={"time": np.array(dates)[:, 0]},
        dims=("time", "lev", "lat", "lon")
    )
    return xmod