Source code for pycif.plugins.datastreams.fluxes.VPRM1km_nc.fetch
import datetime
import glob
import os
from logging import debug, info
import numpy as np
import pandas as pd
from .....utils import path
from .utils import find_valid_file
[docs]
def fetch(ref_dir, ref_file, input_interval, target_dir, tracer=None, **kwargs):
# Inputs:
# ---------
# ref_dir: directory where the original files are found
# ref_file: (template) name of the original files
# input_interval: list of the periods to simulate, each item is the list of the dates of the period
# target_dir: directory where the links to the orginal files are created
#
# Ouputs:
# ---------
# list_files: for each date that begins a period, an array containing the names of the files that are available
# for the dates within this period
# list_dates: for each date that begins a period, an array containing the names of the dates mathcin the files
# listed in list_files
list_period_dates = pd.date_range(
input_interval[0], input_interval[1], freq=tracer.file_freq
)
list_dates = {}
list_files = {}
for dd in list_period_dates:
file = dd.strftime("{}/{}".format(ref_dir, ref_file))
file_hours = pd.date_range(dd, dd + pd.to_timedelta('23h'), freq="1h")
list_dates[dd] = [[hh, hh + datetime.timedelta(hours=1)] for hh in file_hours]
list_files[dd] = [file]
# Fetching
if os.path.isfile(file):
target_file = "{}/{}".format(target_dir, os.path.basename(file))
path.link(file, target_file)
debug(
"Fetched files and dates as follows:\n"
"Dates: {\n"
+ "\n".join(
[
"\n".join(
[" {}:".format(ddi)]
+ [" {}".format(dd) for dd in list_dates[ddi]]
)
for ddi in list_dates
]
)
+ "\n}\n\n"
+ "Files: {\n"
+ "\n".join(
[
"\n".join(
[" {}:".format(ddi)]
+ [" {}".format(dd) for dd in list_files[ddi]]
)
for ddi in list_files
]
)
+ "\n}"
)
return list_files, list_dates