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buoy2csv.py
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buoy2csv.py
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import os
import h5py
import argparse
import numpy as np
import pandas as pd
from datetime import datetime
DRIFTER_ID = 2
def main() -> None:
parser = argparse.ArgumentParser(prog='buoy2csv.py',
description='''buoy.nc to csv''')
parser.add_argument('filename', type=str, help='path to buoy.nc file', metavar='')
args = parser.parse_args()
data_nc = h5py.File(args.filename)
platform_type = np.array(data_nc['platform_type'])
quality_level = np.array(data_nc['quality_level'])
mask = np.logical_and(platform_type == DRIFTER_ID, quality_level >= 4)
year = np.array(data_nc['year'])[mask]
month = np.array(data_nc['month'])[mask]
day = np.array(data_nc['day'])[mask]
hour = np.array(data_nc['hour'])[mask]
minute = np.array(data_nc['minute'])[mask]
second = np.array(data_nc['second'])[mask]
sst = np.array(data_nc['sst'])[mask]
lat = np.array(data_nc['lat'])[mask]
lon = np.array(data_nc['lon'])[mask]
time = []
for i in range(minute.shape[0]):
time.append(datetime(year[i], month[i], day[i], hour[i], minute[i], second[i]))
data = pd.DataFrame({'time': pd.to_datetime(time), 'lat': lat, 'lon': lon, 'sst': sst - 273.15})
data.to_csv(os.path.splitext(args.filename)[0] + '.csv', index=False)
if __name__ == '__main__':
main()