# Climate indicator manager - a package for managing and building climate indicator dashboards.
# Copyright (c) 2022 John Kennedy
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from pathlib import Path
from typing import List
import xarray as xa
import climind.data_types.timeseries as ts
from climind.data_manager.metadata import CombinedMetadata
from climind.readers.generic_reader import read_ts
from datetime import timedelta, datetime
from scipy.signal import savgol_filter
[docs]
def read_monthly_ts(filename: List[Path], metadata: CombinedMetadata) -> ts.TimeSeriesIrregular:
ds = xa.open_dataset(filename[0])
anomalies = (10 * ds.MSL_filtered_GIA_corrected_adjusted.values).tolist()
uncertainty = (10 * ds.uncertainty_envelop.values).tolist()
years = ds.time.dt.year.values.tolist()
months = ds.time.dt.month.values.tolist()
days = ds.time.dt.day.values.tolist()
metadata.creation_message()
outseries = ts.TimeSeriesIrregular(years, months, days, anomalies, metadata=metadata, uncertainty=uncertainty)
return outseries