# 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 numpy as np
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(filenames: List[Path], metadata: CombinedMetadata) -> ts.TimeSeriesMonthly:
ts = read_irregular_ts(filenames, metadata)
ts = ts.make_monthly()
ts.df.drop(ts.df.tail(1).index, inplace=True) # Clip the last month because it is always incomplete except for one day
_, end_date = ts.get_start_and_end_dates()
ts.metadata.dataset['last_month'] = str(end_date)
return ts
[docs]
def read_irregular_ts(filenames: List[Path], metadata: CombinedMetadata) -> ts.TimeSeriesIrregular:
years = []
months = []
days = []
extents = []
with open(filenames[0], 'r') as f:
for line in f:
columns = line.split()
year = int(columns[2])
month = int(columns[0])
day = int(columns[1])
data = float(columns[3])
if data != -9999:
years.append(year)
months.append(month)
days.append(day)
extents.append(data/1e6)
metadata.creation_message()
return ts.TimeSeriesIrregular(years, months, days, extents, metadata=metadata)