Source code for climind.readers.reader_imbie_2021_antarctica

#  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
import numpy as np
from typing import List

import climind.data_types.timeseries as ts

from climind.data_manager.metadata import CombinedMetadata

from climind.readers.generic_reader import read_ts


[docs] def read_monthly_ts(filename: List[Path], metadata: CombinedMetadata, **kwargs) -> ts.TimeSeriesMonthly: if 'first_difference' in kwargs: first_diff = kwargs['first_difference'] else: first_diff = False with open(filename[0], 'r') as in_file: in_file.readline() years = [] months = [] mass_balance = [] uncertainty = [] for line in in_file: columns = line.split(',') decimal_year = float(columns[0]) year_int = int(decimal_year) month = int(np.rint(12. * (decimal_year - year_int) + 1.0)) if not first_diff: data = float(columns[3]) unc = float(columns[4]) else: data = float(columns[1]) unc = float(columns[2]) years.append(year_int) months.append(month) mass_balance.append(data) uncertainty.append(unc) metadata.creation_message() return ts.TimeSeriesMonthly(years, months, mass_balance, metadata=metadata, uncertainty=uncertainty)
[docs] def read_annual_ts(filename: List[Path], metadata: CombinedMetadata, **kwargs) -> ts.TimeSeriesAnnual: monthly = read_monthly_ts(filename, metadata, **kwargs) annual = monthly.make_annual(cumulative=True) return annual