# Climate indicator manager - a package for managing and building climate indicator dashboards.
# Copyright (c) 2023 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
from datetime import date
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_annual_ts(filename: List[Path], metadata: CombinedMetadata) -> ts.TimeSeriesAnnual:
years = []
anomalies = []
with open(filename[0], 'r', encoding="utf8") as f:
for line in f:
if "STNNo. A.D. FiFD FuFD WORK TYPE Name of reference" in line:
break
for line in f:
if line == '\n':
break
year = int(line[6:10])
day = line[23:25]
month = line[21:23]
if day != " " and month != " ":
flower_date = date(year, int(month), int(day))
day_in_year = flower_date.timetuple().tm_yday
years.append(year)
anomalies.append(day_in_year)
years.append(2022)
anomalies.append(date(2022, 4, 1).timetuple().tm_yday)
metadata.creation_message()
return ts.TimeSeriesAnnual(years, anomalies, metadata=metadata)